{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OXYgXFeMgRep"
      },
      "source": [
        "Copyright 2019 Google LLC\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "you may not use this file except in compliance with the License.\n",
        "You may obtain a copy of the License at\n",
        "\n",
        "    https://www.apache.org/licenses/LICENSE-2.0\n",
        "\n",
        "Unless required by applicable law or agreed to in writing, software\n",
        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "See the License for the specific language governing permissions and\n",
        "limitations under the License."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NcIzzCADklYm",
        "outputId": "6fa3998d-f642-40f4-bda5-a06596ccd732"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Cloning into 'google-research'...\n",
            "remote: Enumerating objects: 48, done.\u001b[K\n",
            "remote: Counting objects: 100% (48/48), done.\u001b[K\n",
            "remote: Compressing objects: 100% (43/43), done.\u001b[K\n",
            "remote: Total 18964 (delta 7), reused 45 (delta 4), pack-reused 18916\u001b[K\n",
            "Receiving objects: 100% (18964/18964), 238.22 MiB | 2.03 MiB/s, done.\n",
            "Resolving deltas: 100% (9075/9075), done.\n",
            "Checking out files: 100% (6902/6902), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/google-research/google-research.git"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Rnf4YxsGGJKj"
      },
      "outputs": [],
      "source": [
        "# install tensorflow_model_optimization\n",
        "!pip install tensorflow_model_optimization"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ngihcW7ckrDI"
      },
      "outputs": [],
      "source": [
        "import sys\n",
        "import os\n",
        "import tarfile\n",
        "import urllib\n",
        "import zipfile\n",
        "\n",
        "sys.path.append('./google-research')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y55h79H3XKSt"
      },
      "source": [
        "# End to end example of model training and streaming/(non streaming)  inference with TF/TFlite"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BDP8ai8Ah00k"
      },
      "source": [
        "We will train a simple conv model on artificially generated data and run inference in non streaming and striming modes with TF/TFLite"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fathHzuEgx8_"
      },
      "source": [
        "## Imports"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yP5WBy5O8Za8"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import tensorflow.compat.v1 as tf1\n",
        "import logging\n",
        "from kws_streaming.models import model_params\n",
        "from kws_streaming.models import model_flags\n",
        "from kws_streaming.train import test\n",
        "from kws_streaming import data\n",
        "tf1.disable_eager_execution()\n",
        "from kws_streaming.models import models\n",
        "from kws_streaming.layers import modes\n",
        "from kws_streaming.layers.modes import Modes\n",
        "from kws_streaming.layers import speech_features\n",
        "from kws_streaming.layers.stream import Stream\n",
        "from kws_streaming.models import utils"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jow_HMLAU7LR"
      },
      "outputs": [],
      "source": [
        "config = tf1.ConfigProto()\n",
        "config.gpu_options.allow_growth = True\n",
        "sess = tf1.Session(config=config)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zMdTK10tL2Dz"
      },
      "outputs": [],
      "source": [
        "# general imports\n",
        "import matplotlib.pyplot as plt\n",
        "import os\n",
        "import json\n",
        "import numpy as np\n",
        "import scipy as scipy\n",
        "import scipy.io.wavfile as wav\n",
        "import scipy.signal"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "L_F-8OFCU7La",
        "outputId": "4e8e8965-186b-402a-af5d-76443da9e4ef"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'2.5.0-dev20200629'"
            ]
          },
          "execution_count": 218,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.__version__"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xHTcbg_ao586"
      },
      "outputs": [],
      "source": [
        "tf1.reset_default_graph()\n",
        "sess = tf1.Session()\n",
        "tf1.keras.backend.set_session(sess)\n",
        "tf1.keras.backend.set_learning_phase(0)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ylPGCTPLh41F"
      },
      "source": [
        "## Prepare artificial train data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8kw_Z0AOh005"
      },
      "outputs": [],
      "source": [
        "samplerate = 16000\n",
        "singnal_len = samplerate # it is equalent to 1 second\n",
        "\n",
        "label_count = 4\n",
        "train_data = []\n",
        "train_label = []\n",
        "data_size = 1024\n",
        "for b in range(data_size):\n",
        "  noise = np.random.normal(size = singnal_len, scale = 0.2)\n",
        "  label = np.mod(b, label_count)\n",
        "  frequency = (label+1)*2\n",
        "  \n",
        "  signal = np.cos(2.0*np.pi*frequency*np.arange(samplerate)/samplerate) + noise\n",
        "  train_data.append(signal)\n",
        "  train_label.append(label)\n",
        "\n",
        "train_data = np.array(train_data)\n",
        "train_label = np.array(train_label)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "r2yeKkLsiRWJ",
        "outputId": "7b158874-47fb-417f-c240-dfd5db31c9e5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "label 0\n"
          ]
        },
        {
          "data": {
            "image/png": 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VqyH3VwAJQoirAKwC8JW7A4UQc4UQSUKIpNjYWJ8LHNyhKX58aDAAoI/TCLfwesE+v6637KfAraiswvniMpRWmOeqItB5+spuHW1J+m/d1MvtMQkxETJG5Nrl0gr8fuQM8i6W4DhPU1EnWlyOrXriapf7G9dXb3IEOUrKBWB/5d5K2mcjhLDvrP4ZgLdkKNejfm2jkZ08CU8s2I0/jlfPh9OkQT1ccJqeN0Shen77aqSOUmNk/4Qm+N+DQxQpz0iSl6djRCffv/h9IbxMBSM6xWLT4TNo3cR1r4u7BreVIyyP/vG/PVhuNzOk1leTepd/sQSPzftD9XIT4xu53N8xzvV+Jchxpb8DQCIRtSOiUAC3AfjF/gAiam738HoAB2Uo12uPju7o9jnrFZsadmSfQ4UJG5C8kX76Ij7ZcARTP92marneDgC7d1g7pMwcg/axDV2/nl1Xn54tG2Ns13i/4nMn43SRw+OEGUtxvrhMkbKM4Nvt2s3NZe+zO5NsNRJq8TvpCyEqADwCYCUsyfwHIUQaEb1CRNdLhz1GRGlEtAfAYwDu9rdcuXVppt43LQAs3XeKq3lcyD5zGbfM2YpT50tUK3Oy3WCr+qHeVf0REeIaOfbb/+nhmndxqc+NxY8PDcF7t7qvBpLbicIrqpXFfDO2Wzz6tXXfbqQEWer0hRDLhBCdhBAdhBCvSfteEEL8Im0/I4ToLoToJYQYJYRIl6NcbzVrbPlwPnlN5xrPNW3oviFOCe+tOoTOz62oUc1kdiPfWY+Uo4V4fvF+1cp875beDo93PjfWr9fr26aJbdvanhTTMAyhIUGIDFdmjhXrHE+spkN5Rfh6a7bjThNPX2HIEbnuhIcEIzt5Eq7vpf0w+mNSY1vhZcdb8CtllUg5WqhFSLqSc069q1TnLr4OFwBe5oaeLS2jwa0TaA1PVLdNwp637RNGNeGDTXhhcRoAYPm+U5jx415Vyu3dWtkpkn1lqqTvysjOsVjy6DCtw7B5euEe3DJnK06eN9+t+fcq17OO6x4v699+/8vjsFCqn20g9RBz1ULwwIj2spXJPLPvTPHQd7ss03koNKx6Ys9mAICI0GD8PH2oLhvUTZX07f/Oyx8fjoHtovHR7X3Ro6V+5uo5eMrSd7i4rELjSNS181gh5mxUd+rkiT2be/7be5EbGoaFICzEkuy/u38Q/m98ZzSJCHXxkpYXndCjWd1f3AcbMngiNrcUqt556bruAIAGdqO4F0ltPHcPSVCkTG+ZKunb69o8EgseGIyIMEMuHhZwbvx4q63KSw+st+YRXjbsWrWLicDDI133FrNefCh9sfHuqkOKvn4gO6JQG4irr5I+bZogO3kSXrq+uyJlesu0Sd+VlX93PXBCSc4XkkcKzNcgt3yfNgvM1LZ85YMjOgAA6gUH9kfkwpVynnLEhaV7lX3P6WxOPgeB/Y72kqc7us4qd9sEeJIGwFLPqqRv7h3gcr+K8+45ULPYXi//hld+TXPYJ4TApxuzcIHXejAlUyV9Zj5jusS57EFzz9AEjOvuvk49NMSSmhv4WL1TF8LpKiTaRf2/HH51uqrdeuQsXlt2EDN/3qdIeXp1QJprR0neNBWEanQXaaqk72uD/eypfeQNhKnG3d/8xeu611p1M7JTHJ76Uye8fL38E/G5i+neYe1kLwuo/nJ5YsFuTPxgE0ql0eBFJebqLDBx9ibVyvKUa7Y+Mxrbnx2jTjBOTJH0G4VbGmutPSu8oXS/fj3X/RlBbfX29q7v1QL32SXdoCDCo2MS0VjBBauFcLy6n9LH1eS08ln0Ry4OnFL+apd51rxxfZc9u9RgiqT/z/FdMGNCF7+6yD1/rat1YZRj1AGD54vLMOzNtUg7eUGV8uo6o+rsqX3wnEp/Y3fz+7SMql/rVM6+MuhbSZeaNgxFQtMGmDWlp9ahuGWKpB8RFoIHR3RAkB8td0rdei/6I9d2+22GCbK2ZJ5Fzrkr+GhdpirltYyqOfvlqM7ajZJ1NveOfg6Pv7ynvyLl5F1Uby4jM6sXHIT1T4/Cn7opM7GeHLiTei02PD1S8TI+WHMYsY3C8NdBbR2mxmXycK7d2f7sGDSur1yVTV1Muqo5PlyXiWu6N6vRY6xBqPwfyfPF5Rj4+hrb49JynuFVbsk39MSkq5p7PlAHOOnXom1T5Re/AIDnft6v+OhMvSqrUDYBdZeWOtz2zBicOFeM+MhwD7+hvK7NIzUdnu883xPz35Q+LVVdnMkfpqje8cbP04dqUm6/Waux89g5TcrWwsUrFej54kp0em65ouVce5WlEb5Z43D0T1B3Clu9MtNEbGqtWxEoCR/gpF+DljPj/bLnpGZlq8Va3bL/5AUUlZqry2BdvX9rb9wxqC2aKNRzyKidBFxZkHrC80Emw9U7LsyfNsjlB2N4Ygw2HT6jXMF2ZRp15Lz1vHJXVUdNnbpuTunTEl2bR+LZRfIPoDLoW6uGsooqHMk337QmnvCVvguD2jfF4A5Na+z/cGpf1WJYn5GvWllaqGv/eW/pcSpbT9JfHY/fnxldY/+t/Vu7OJrV1S1ztuKLLUcVL2fWFPkH8CmJk76e2OXBCoNe6ltzvRqNiY+Mcr8msp6E1wt2OXDQeXEX2RiwfmfCB5vw0i/VcwydKCzG7hPnVSl7dJc4VcqRCyd9L0SE1fxgDusYI9vrK92TxejSXh7n8Njac4c5en5xmueDAszBUxfx39+zbY/PXCpVrWyFbloVw0nfCyFOc7VEhoco/gef/t0uJMxYqmwhBsFrIzAtuBthrVeyJH0iGk9EGUSUSUQzXDwfRkQLpOe3E1GCHOVqbeP/jVLsta1fJks1mmuemUNxWQWulFVqHYbs9qhUtROI/E76RBQM4CMAEwB0AzCViJwnMbkXwDkhREcA/wLwpr/l6kFUg1DdLIHGqrWOrjn1AnOt2wsr0fOllVqHIbuXfj2gWllmrN4ZACBTCJElhCgDMB/AZKdjJgP4StpeCGAMKdV9Q2XDEuWr07dHIFws4UUu6sp+aoXuzfWz5nEgMFqnASXnzV//j5E19gVaIpMj6bcEYD8CIkfa5/IYIUQFgAsAavaJDEDBCn13EQFfbclW5LWN5NXJlnVHuXsjs1Jq3vxbklohJDjQUnxNumvIJaJpRJRKRKkFBQVah+ORc+OuXAiOC1sHcs8e+xWi5P7IdGsRifRXx2PG+C4yv7I+fHPvAPzjmk6KvHZqdqFt+73fMpAwY6kpZnr11Vs39XJ4bBtQF2DfA3JkrFwA9pdZraR9Lo8hohAAjQGcdfViQoi5QogkIURSbKx+psB19uNDg1Ut7z/r1ZmKWG6Z+ZfQ7plltsXP5a5J6Nc2GuH1gv2aNlvPhifG4pHRiZg5savsr33ZrgF39lrL+yvn3BXZyzGillH1A64u30qOpL8DQCIRtSOiUAC3AfjF6ZhfANwlbd8EYK1wXiA0QFzVylJf3K9tzcm7xsg4SOON5ekOj88F6MyI+3Mti6V8u/0YAGD698ougg4AY6W5zBPj1V/onhkLETCuu+u58WdP7YOhHZuiaUSYylH5x++OzUKICiJ6BMBKAMEAvhBCpBHRKwBShRC/APgcwDdElAmgEJYvhoC0YNpgXC5Tf6Kw0ooqVFYJ5UZpKmxL5ll8ujFLlbJu6tcKE3s2U2Rueq1Yl/xUmv2lWEFRKaqE0MV01FoZkBCNf0/ti8suJgcc0iEGQzoo05FDSbJUSAshlgkhOgkhOgghXpP2vSAlfAghSoQQNwshOgohBggh1Pn0K6B+aDBiGrr+Zr+xXyvFyp2/4wQ6PLtMsddXwrJ9p3ClvLoK4bVlB1Ur20gJHwBuTlKnodp+2uX+r612WHxFr7ZkVk+COOED+RtxQ0OCbOvZhkpteHGRgXV1b89YnwyNTewZGCvnqGHX8XN4+LtdCK+nu74CASlQ7/CUVlZRhb98tt32+KDMC78719vHRYbj/Vt7K9ZVWw38iWSKKCqx3A6XKLg03z8N2mPHnSm9WyhexvUfbsE6pxleizWozqwrpRfhcWVKn5Zu7/YDASd9GfRoGYl+bZtoHYauqHFd+tDIDiqUoh/v3tIbj41JVLyc1QfyHB5/vP6I4mXqVWB2N6kdV+/IYMmjw7UOQXcCtTubngUHEWIbqX+FWabSkoNMHXylzwLSv27t5fkg5pMaX9gGvNqtKyNevHDSDzCBMmJS6elm/9xHuZ5SgeTfU/vI/pqH8y6hUsfz8SzenavKeA+j4qQfYHq/skrrEJiOtGoi/4yi248WYvaaw7K/rlwen78bS/fylOO+4qTPFKHkbXGIibsvto+JsG1veHokghQ60WotNeitSy4GSSnJiA25nPRltnj6UNWW6Zs0exPu/zpVlbK8pWRaNmI9a10NtVueMywkGA1VGqlrlXG6CKcuaDc/T48Xq+f+f+7nfZrFEcg46cusV+soLHl0GFY/OULRcioqq5B28iJWOXWvU9rOY4Uuh6SrySBLMciiQ2xDRV7X3Wpa497fiMFvrFWkTG99u+244mUY8a3GSV8BRISOccp8GK2eX7xf0dd3pfByGW78eCsen/+H22NWpp3GzmPnFL3UN3HtjksvX99d9tdMsZt22WpfzgXZy2Hq46QfoOalnPB8kMxKpHl09udeRLmbvtsPfLMTN378u6K9d+7iJSodqHU+3liu3txJ9m75ZCuSnWadZb7jpB+Atme5XIrAK8fPFuPMpVKffvf0xRIkzlyOkvJKzEs5jl/3nKxxTIGPr10XRl0wRc9eXXIAvx/x/33ni5TsQnyyQb1RwX3bRNm2Oxtwem4ekRuAbp27zevfOXXhCrLPFGNwB8sqlVe/vQ5BBGS9ManOr+HckeHClXI885OlMe26Xo7zwjw2z30VkK8WTx+KvbkXuE5fZQLA55uPqlJWWUUVft6di5v7tUJJeRU2HKqeB+j91Ydq+U35tYuJwMxJ3VQtUw2c9A1ACOExEV7z3kYUlVYgO7k6yfs7/mb4m+ts2+mnL2JH9jn/XtCDDnEN0at1lOcDmeIqKqtkWSq0skpg1tIDuG94e7SMqo+P1mXigzWHERYShK1HzmL+jupqzPdXKzd24Mt7+mPNwTx8u+04urWIxK7j59E/oQlCQ4xXGWK8/5GOpDw7RpVycs5dQcKMpViXnu/2mCIFetzYz8ky/v1NeP5n9RuXmcX0UcpNPqfkfdWu4+fw5ZZsPLFgNwDYqhxPni9xSPhKG9U5DrOm9MSeF69Bz5aNVStXC5z0FRRWL1iVcqxLEs7ZqGy9pxaVKsFBhJulxWlCFVqE3gimj+qo2Gs7T7UsJ+vgJ+fVU99coV7Drf00yY3r10P3FpakP6KTfMuf6glX7xjAEmnR8W1ZhZj+/S70aNHYYdphudbX1WJw4pHXJ6KqSuDVKT0MeastFyVXCjuUd6nGPnfvhSV7T+KD1Yex8u9XB8xi9c5LUfZo2RgHXhlnuNXXrIz5v9IJtdob7echWbr3FJbuPeWQ9E9dKFEnEIUEBRHCg9S5a2K+WZueh4e/22VbNKe8qgphtfzNLpdWYMX+02gd3UCtEN1yvssAjLfcpj2+dFKQUvOimMUtSTyTpisLHxyMMV3iNJlb38o5T76z8pBXq6Q9v3g/nvrfHstAPttrCmw6fKaW32Jy4KSvoIZhIXhlcneseuJqTcq/VFqBcf/aWOu6oZVVos7VP66uiJTUyYB9pOWQlBCNz+/ur+m6ufd9nep2qgZnFZVVOO10t5l/0dJga78U46oDeTheWCxfkHVkti7AfiV9IoomolVEdFj61+WagURUSUS7pZ9f/Ckz0Nw5OAGJGiSv7VlnsWhXDjLyivDPH/e6Pe7VJQfQ59VVHmcvrKiswjC7LprM3DYeKsDaWnqL2V8fPL1wLwa9scbhqv5iSTkAYJnUHrUj+xxOX9SmGlLtixmt+XulPwPAGiFEIoA10mNXrggheks/1/tZJquDW+duw/OL0wAAFXYd8ksrHK/OlkofOk+TqP3iYtQt05fnJnXFEGnwnZ4s+iMXgGOPnL3SPD5HCi7b9tl/KajhuUldVS1PL/xN+pMBfCVtfwVgip+vxxR22KknhvXG1tPFTmkFr5Oqd/cNb6/q4GkBy4EAABPMSURBVLXzV8pwKK+o1mMc5uX38B5Te/ZWs1XrWPmb9OOFENauI6cBxLs5LpyIUoloGxHV+sVARNOkY1MLCgr8DI852+Y0b4/1fS9cfCKLyyrQ/YUVWHMwD3ka3Xoz7zRQaWwIAMxctB/X/GtjrdN7z7GfM8djjlU3CQdLxTUKr6dquVrz2C+JiFYDaObiqZn2D4QQgojcfZe3FULkElF7AGuJaJ8QwuVIIiHEXABzASApKclwlW3ZyZMghEC7Z5ZpUv6spQdx3/D2tsfW2TDtr/RLyiuxcGcO+rSJwuWySry9MgPpp2u/opPLq1N68MheP2jRN/7+r1MRH+nYkygz/xKOFNTs318btS+8W0c3wHOTumLSVc3VLVhjHpO+EGKsu+eIKI+ImgshThFRcwAuW3aEELnSv1lEtB5AHwDqTZvHHHhquHpnZQY+23wUj41JVCmianEadkM0Aq1GLZc5Vf9d++/NAICJPauvFz3ldLUXBCKCwwWQWfj7DvkFwF3S9l0AFjsfQERNiChM2o4BMBTAAT/LZX5wd5ex+8R5TP9ul21a5CtSdzq1rvIBY65JqqY7BrfVpNxzxeUu9yu5rgLzjb/DzpIB/EBE9wI4BuAWACCiJAAPCiHuA9AVwBwiqoLlSyZZCGG6pL/mqRHIzPfudlcN1XX6wJSPtgConovErA1dgSxcxTr9OrF7C/HbSR/8SvpCiLMAakwlKYRIBXCftP07gJ7+lGMEHWIbKraeqT+qe+9UX2JbZzqcuzFL/XjsEkMYz7UT8Ozz/LasQpwoLNbF1AsA0D8hWusQNMGfKg21aByudQg4qbN5eYQAPr8rCR3jGuK2AW20Dicg3dC3pdYh2DjfLb63St2FUJw1CLXcCXVrHmm6XjtWnPQ1QET46Pa+WPjQEK1DsflUg6t6d8Z0jcfqJ0egHk+l7JP3bumtdQg2peWOgwHPXCpFwoylGkUDrP/HSADA6C7GnDa5Low7lZzO6a2b2Fdbj2kdAjOg35x65Gg9oVpcZDh2zByLphGhmsahJU76jDFT0XJ2Uj3g+2fGDCyqgTnrrZl7nPR1gpcCZEqIMPBiIMw3nGl05JO/9tM6BE39ZWAbjOlq3gY2xtTASV9j8+4fBAAY2N6cfYbtvfbnntxjR2ZmmyvelZZR9QFYFj1n3JCrucEdmmLVE1ejZZP6OHleX33mWeDjlA80axyOUV1icVt/HvcBcNLXBevKWh3j9DdilwU2vtC3jAqeNcX0kwLY8L00Y8zQeM4fR5z0GTMw6+I4K/4+XONImF5w0mfMBKLqm3cE6l8HaTPdtF5x0mfMwMxYp//knzrZtrOTJ2Fyb/1MQKcHnPR1alx3d8sNG8eozrG27XYxERpGYjyju8QhMry6n4aZ6rXt/9+sJj47OhVt0Amhnp3YBa8vS8eR1yciOIhQVlGFlKOFGJYYo3VohvLF3f0BADuyCzFnwxHbwjhm8JdBbfHl79kY2pHfU67wlb7OPDHWcmva2IB1sMMTYzDt6g7ITp6EYGkB79CQIE74CuqfEI3P7upvO9/2npnQRYOIlFcvOAgbnh6F1//M3TRd4aSvM6HSalFGHEk5sae+ppM2uwdGdNA6BKYBTvo6Y6a6V6adJY8O0zoERUSE6myNYB3ipK8zY7taGnCvvaoFGoZxkwuTX3byJPRo2VjrMGT3xg098atBv8zkxFlFZzrGNUR28iQAjotKM8ZqN5XXVK4Tv670iehmIkojoioiSqrluPFElEFEmUQ0w58yGWOM+c7f6p39AG4AsNHdAUQUDOAjABMAdAMwlYi6+VmuKbRp2sC2nZ08Cb1aR2kYDQt0i6cPxad3Ol6bcRuS+fiV9IUQB4UQGR4OGwAgUwiRJYQoAzAfwGR/yjWLr/42wOFxI67jZ37o1ToKf+pm/EF/rHZqNOS2BHDC7nGOtM8lIppGRKlElFpQUKB4cHrmPKBGBPjs6NbFLJh+GLBnMPPA46UjEa0G0MzFUzOFEIvlDkgIMRfAXABISkrit6SdQP+AXt0p1vNBjDFFeUz6QoixfpaRC6C13eNW0j7mpapAz/pMd2IahuLMpTIMSIhGSnah1uEwFahRSbwDQCIRtYMl2d8G4HYVyjWEz+5MQkNpAqmqAM75zSLDtQ6BufDTQ0OxMu007hzSFp2fW6F1OEwF/nbZ/DMR5QAYDGApEa2U9rcgomUAIISoAPAIgJUADgL4QQiR5l/Y5jG2WzwGtW8KAKhfL3BHGzYIC9zYjaxN0wa4/+r2CAvhv49Z+Nt7Z5EQopUQIkwIES+EGCftPymEmGh33DIhRCchRAchxGv+Bm1WYSGBNYD65n6tbNvcMzCwDOdJ8AwrsLKIyQ0PsIbQFlH1cfeQBABA6+gGtR/MNHddrxYAgPdu6YXkG6/SOBqmFE76AeSvA9tg53P+tqurhwi2qql6wfxW07sQu+mXuXutcfEnMYAQEZo2DMObN+pznvDHxiS6fY6rd/TPiNN5s5o46QegW/u3sU3Kpif2a5OywMVTMxgbJ32mGOLre6aA5yZ1BQDc1r+1hyOZK5z0DcD6IdCjbs0jAVQ3EjL9cq7c6RTfEP3aNtEkltq0i4kAACRI/zLvcNI3gDgdDXxaMG0QbuhjmVqJyNIPPDt5Eif9AGK9Q/vtiRH46Pa+GkcDdI5v5PB4TNd4fHvvQEwb3t62b0iHpmqHFbA46TNZDWzfFM2jLF9CXLkTWCb0sKxhrKdVtYKouo3h2qua274AhiXGICiIMKqzpRvzF3f31yrEgMNz9TLFcINgYBnfoxmOvjERZPeH03pAYGhIEJ4e1xmPzvsDb910FRqEOqasj//aDwVFpQgP4NHqauMrfYOyDopSin2fbme9W1vqgfV0xcjqhpy+qZtEhOKbex3XdYgIDVa199iYrvE48Mr4GgkfAMLrBfPAPy9x0jcAV/2ra0vKcmhcv57b5/7ULR7bnhmDkZ3jFI2BqWN4Yiy+vIerT4yCk75BaV210qyxfhqXmf+6Nou0bb8yuQcAYO1TI7QKh/mBk75BfH//QKyx+xB2curxILdhPCGXKcVHhuFGaSI956ogJfAgYflx0jeAxLhGGNIhBh1iG9r29W4dhe4tLFdnzl3efBVer/rtYp1Th7timoO1tjDCRb06Cyyc9APYnDv64bpeLdCtRWSN5zrENkRcozAXv+W7kKDqt4v1CiwilHtNmEFcZDiemdAFX/2tulHX2+t8T+9HV33t+UJffpz0A9i47s3w76l9XD4XZNeQK9dduP3LWBdp17rtgKnngREdau0p08ZDL5qwerWnm8m9q+8aa+sowPzD92oGs/rJETh7qRRA9VVSwzCZ/swuEzxnfbNy/sLvnxCN44XFbo+vrX7+yOsTERxE+OeP+5x+yY8AmUt8pW8wHeMaYmB7x9vk++yGq/vD4Urf7sO4YNognmHThJzXSPjroDa4Ncn9JGjW6Tmcrfz71QhWuIsxq8ZJ3wScR1X+bWg7n17HvreGsO2zTL1Q21z6zJhaRNXH+7f2RtOIUABARFgI3rzJ/YpbY7rG27Y3/3MUAMtiLZ2bVXc02P7sGNzUrxXmTxsEALhnaIICkZsbJ30Dc3U7veHpkXjhum5uf8d+XVtn1mqikCDC+O7N0DKqPu4d5tsXCDOGKX1aIlpK+t4Ile4SmjuN54iPDMc7N/dC1+aROPrGRMyY0EWWOFk1v5I+Ed1MRGlEVEVESbUcl01E+4hoNxGl+lMm84HdnXPbprVPR1vb1Al92kQBsAzOiW0Uhi0zRjt0E2WsruIiwzF7ah/MuaOf22OISJWxAGbj75X+fgA3ANhYh2NHCSF6CyHcfjkweVmvwFxNmpUY55is+7VtglGdY/GXgW3cvp71AxgRxt00WbW6rn9sX40DANf3aoGmDeXtVsw886tbhxDiIKDOyDzmvVcmd0efNlEY3L5m/+eFDw7By7+m4ac/cgEAPz40xO3rJN/QE//9PZv76TCX5tzRD/NSjte4kHDGM2Hqg1p1+gLAb0S0k4im1XYgEU0jolQiSi0oKFApPGNqFF4Pdw5OcPml3LhBPSR6GKl7z9AE3DusHW4b0AYr/n41Okof6liZB32xwNY6ugH+b3wX2/usQyyvaKVnHq/0iWg1gGYunpophFhcx3KGCSFyiSgOwCoiShdCuKwSEkLMBTAXAJKSkriXroZevK67w+Ppozqif0I0BvMqRawWa54aiR935uCp/+2x7buplg4CTF0ek74QYqy/hQghcqV/84loEYABqFs7AFNQkwbejXoMDiJO+KxOnG8ueeI0/VC8eoeIIoiokXUbwDWwNAAzFX1+VxJemex45X5LLQNpGPPH1Z1itQ6BueFvl80/E1EOgMEAlhLRSml/CyJaJh0WD2AzEe0BkAJgqRBihT/lMu+N6RqPOwcnOOwL4lGQTCExDcNsbUBMX/ztvbMIwCIX+08CmChtZwHo5U85jLHAY7+im3WCvk7xDXEo75JWITHwhGuMMYW4qsb/5ZFhKKusUj0WVo2TPmNMGXZZv1cry2ju8HrB3F9fY5z0Tc7V7fYPDwxGRRVfjTH/WJP7Z3cmYUzXOI2jYVac9E1u0cNDcam0wmHfgHbRGkXDjGTunf3w485cjOkax6P2dYSTvslFhIUgQq5FVhiz06pJAzw+lqfc1hueWpkxxkyEkz5jjJkIJ33GGDMRTvqMMWYinPQZY8xEOOkzxpiJcNJnjDET4aTPGGMmQkLHqxsQUQGAYz7+egyAMzKGIxeOyzscl3c4Lu8YMa62Qgi3CxroOun7g4hShRBJWsfhjOPyDsflHY7LO2aMi6t3GGPMRDjpM8aYiRg56c/VOgA3OC7vcFze4bi8Y7q4DFunzxhjrCYjX+kzxhhzwkmfMcZMxHBJn4jGE1EGEWUS0QwVymtNROuI6AARpRHR49L+aCJaRUSHpX+bSPuJiGZL8e0lor52r3WXdPxhIrpLpviCiegPIloiPW5HRNul8hcQUai0P0x6nCk9n2D3Gs9I+zOIaJwMMUUR0UIiSieig0Q0WA/ni4iekP6G+4loHhGFa3G+iOgLIsonov12+2Q7P0TUj4j2Sb8zm+q4rJWbuN6W/o57iWgREUV5Og/uPqPuzrWvsdk99xQRCSKK0cM5k/Y/Kp23NCJ6S9VzJoQwzA+AYABHALQHEApgD4BuCpfZHEBfabsRgEMAugF4C8AMaf8MAG9K2xMBLAdAAAYB2C7tjwaQJf3bRNpuIkN8TwL4HsAS6fEPAG6Ttj8B8JC0/TCAT6Tt2wAskLa7SecxDEA76fwG+xnTVwDuk7ZDAURpfb4AtARwFEB9u/N0txbnC8DVAPoC2G+3T7bzAyBFOpak353gR1zXAAiRtt+0i8vleUAtn1F359rX2KT9rQGshGWQZ4xOztkoAKsBhEmP49Q8Z4olQy1+AAwGsNLu8TMAnlE5hsUA/gQgA0BzaV9zABnS9hwAU+2Oz5Cenwpgjt1+h+N8jKUVgDUARgNYIr1hz9h9SG3nS/pgDJa2Q6TjyPkc2h/nY0yNYUmu5LRf0/MFS9I/IX3gQ6TzNU6r8wUgwSlRyHJ+pOfS7fY7HOdtXE7P/RnAd9K2y/MAN5/R2t6b/sQGYCGAXgCyUZ30NT1nsCTqsS6OU+WcGa16x/rBtcqR9qlCusXvA2A7gHghxCnpqdMA4qVtdzEqEfv7AP4PQJX0uCmA80II60ro9mXYypeevyAdL3dc7QAUAPiSLNVOnxFRBDQ+X0KIXADvADgO4BQs//+d0P58Wcl1flpK23LHBwB/g+Uq2Je4antv+oSIJgPIFULscXpK63PWCcBwqVpmAxH19zEun86Z0ZK+ZoioIYAfAfxdCHHR/jlh+RpWtW8sEV0LIF8IsVPNcusgBJbb3Y+FEH0AXIalusJGo/PVBMBkWL6UWgCIADBezRjqSovz4wkRzQRQAeA7rWMBACJqAOBZAC9oHYsLIbDcUQ4C8DSAH+raRiAHoyX9XFjq8KxaSfsURUT1YEn43wkhfpJ25xFRc+n55gDyPcQod+xDAVxPRNkA5sNSxfMBgCgiCnFRhq186fnGAM4qEFcOgBwhxHbp8UJYvgS0Pl9jARwVQhQIIcoB/ATLOdT6fFnJdX5ypW3Z4iOiuwFcC+Av0heSL3Gdhftz7YsOsHyB75E+A60A7CKiZj7EJvc5ywHwk7BIgeVOPMaHuHw7Z97WNer5B5Zv0CxY/tjWBo/uCpdJAL4G8L7T/rfh2PD2lrQ9CY6NSCnS/mhY6rqbSD9HAUTLFONIVDfk/g+ODT8PS9vT4dgw+YO03R2OjUtZ8L8hdxOAztL2S9K50vR8ARgIIA1AA6msrwA8qtX5Qs16YNnOD2o2Sk70I67xAA4AiHU6zuV5QC2fUXfn2tfYnJ7LRnWdvtbn7EEAr0jbnWCpuiG1zpliyVCrH1ha5g/B0to9U4XyhsFyq70XwG7pZyIs9W1rAByGpaXe+uYhAB9J8e0DkGT3Wn8DkCn93CNjjCNRnfTbS2/gTOkNY+1BEC49zpSeb2/3+zOleDNQx14LHuLpDSBVOmc/Sx8wzc8XgJcBpAPYD+Ab6cOn+vkCMA+WdoVyWK4K75Xz/ABIkv6PRwB8CKdGdS/jyoQlaVnf+594Og9w8xl1d659jc3p+WxUJ32tz1kogG+l19sFYLSa54ynYWCMMRMxWp0+Y4yxWnDSZ4wxE+GkzxhjJsJJnzHGTISTPmOMmQgnfcYYMxFO+owxZiL/D3fdpsLpxK7DAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "\u003cFigure size 432x288 with 1 Axes\u003e"
            ]
          },
          "metadata": {
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "ind = 0\n",
        "plt.plot(train_data[ind])\n",
        "print(\"label \" + str(train_label[ind]))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5_wbAZ3vhQh1"
      },
      "source": [
        "## Prepare non streaming batched model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CLwVDzGHh01A"
      },
      "outputs": [],
      "source": [
        "FLAGS = model_params.Params()\n",
        "flags = model_flags.update_flags(FLAGS)\n",
        "flags.desired_samples = singnal_len\n",
        "epsilon = 0.0001\n",
        "batch_size = 16"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SYl2VSAhU7L_"
      },
      "outputs": [],
      "source": [
        "input_audio = tf.keras.layers.Input(shape=(singnal_len,), batch_size=batch_size)\n",
        "net = input_audio\n",
        "net = speech_features.SpeechFeatures(speech_features.SpeechFeatures.get_params(flags))(net)\n",
        "\n",
        "net = tf.keras.backend.expand_dims(net)\n",
        "net = Stream(cell=tf.keras.layers.Conv2D( filters=5, kernel_size=(3,3), activation='linear'))(net)\n",
        "net = tf.keras.layers.BatchNormalization(epsilon=epsilon)(net)\n",
        "net = tf.keras.layers.ReLU(6.)(net)\n",
        "net = Stream(cell=tf.keras.layers.Flatten())(net)\n",
        "net = tf.keras.layers.Dense(units=label_count)(net)\n",
        "model_non_stream_batch = tf.keras.Model(input_audio, net)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "szwNhX8Sh01H"
      },
      "outputs": [],
      "source": [
        "loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)\n",
        "optimizer = tf.keras.optimizers.Adam(epsilon=flags.optimizer_epsilon)\n",
        "model_non_stream_batch.compile(optimizer=optimizer, loss=loss, metrics=['accuracy'])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6Hf3osmCh01J"
      },
      "source": [
        "## Train non streaming batched model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vq6e1Bayh01K",
        "outputId": "d134d7b8-4c6e-4028-e6da-b5118cb99c97"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "accuracy on training batch 18.75\n",
            "accuracy on training batch 25.0\n",
            "accuracy on training batch 25.0\n",
            "accuracy on training batch 31.25\n",
            "accuracy on training batch 50.0\n",
            "accuracy on training batch 62.5\n",
            "accuracy on training batch 68.75\n",
            "accuracy on training batch 87.5\n",
            "accuracy on training batch 87.5\n",
            "accuracy on training batch 75.0\n",
            "accuracy on training batch 81.25\n",
            "accuracy on training batch 87.5\n",
            "accuracy on training batch 87.5\n"
          ]
        }
      ],
      "source": [
        "# we just overfit the model on artificial data\n",
        "for i in range(data_size//batch_size):\n",
        "  ind = i * batch_size\n",
        "  train_data_batch = train_data[ind:ind+batch_size,]\n",
        "  train_label_batch = train_label[ind:ind+batch_size,]\n",
        "  result = model_non_stream_batch.train_on_batch(train_data_batch, train_label_batch)\n",
        "  if not (i % 5):\n",
        "    print(\"accuracy on training batch \" + str(result[1] * 100))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QVhESthmMl0X",
        "outputId": "ab9c5b79-8719-4e69-dbeb-7d779f29c29f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "\u003cIPython.core.display.Image object\u003e"
            ]
          },
          "execution_count": 239,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.keras.utils.plot_model(\n",
        "    model_non_stream_batch,\n",
        "    show_shapes=True,\n",
        "    show_layer_names=True,\n",
        "    expand_nested=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RIr1DWLisMu9"
      },
      "source": [
        "## Run inference with TF"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "456ynjRxmdVc"
      },
      "source": [
        "### TF Run non streaming inference"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-vJpOCJClDK5"
      },
      "outputs": [],
      "source": [
        "# convert model to inference mode with batch one\n",
        "inference_batch_size = 1\n",
        "tf.keras.backend.set_learning_phase(0)\n",
        "flags.batch_size = inference_batch_size  # set batch size\n",
        "\n",
        "model_non_stream = utils.to_streaming_inference(model_non_stream_batch, flags, Modes.NON_STREAM_INFERENCE)\n",
        "#model_non_stream.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "O1gOGQjWMufh",
        "outputId": "8d33b264-09fb-496e-8837-015aca5c79fc"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "\u003cIPython.core.display.Image object\u003e"
            ]
          },
          "execution_count": 241,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.keras.utils.plot_model(\n",
        "    model_non_stream,\n",
        "    show_shapes=True,\n",
        "    show_layer_names=True,\n",
        "    expand_nested=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nPUfT4a4lxIj"
      },
      "outputs": [],
      "source": [
        "predictions = model_non_stream.predict(train_data)\n",
        "predicted_labels = np.argmax(predictions, axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "63sisD1hl7jz",
        "outputId": "13d6525c-bdec-4a13-b0ce-ea6caad721cc"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([0, 1, 2, ..., 1, 2, 3])"
            ]
          },
          "execution_count": 243,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "predicted_labels"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Pt3CDbaJh01f",
        "outputId": "91f21d5b-dfcb-4d99-82c1-c64e0009576a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "accuracy 93.5546875\n"
          ]
        }
      ],
      "source": [
        "accuracy = np.sum(predicted_labels==train_label)/len(train_label)\n",
        "print(\"accuracy \" + str(accuracy * 100))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZVFoVdYSpnL_"
      },
      "source": [
        "### TF Run streaming inference with internal state"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cgcpcrASquAY"
      },
      "outputs": [],
      "source": [
        "# convert model to streaming mode\n",
        "flags.batch_size = inference_batch_size  # set batch size\n",
        "\n",
        "model_stream = utils.to_streaming_inference(model_non_stream_batch, flags, Modes.STREAM_INTERNAL_STATE_INFERENCE)\n",
        "#model_stream.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BNtgTOBCM06v",
        "outputId": "c633612b-bcfb-4e50-808f-6a1f7e9e2a1a"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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Dhw+1VH7u3LkhQ4a0adOme/fuMTExw4YNmz179qlTp0pKSsT7VVxcXFJSEhYW5uXltWTJkrCwsBUrVpSXl7Ptnjx50tHRMS0trXqTvvvuu4iICFbP1KlT//Of/8jlcoMeorS0tHHjxrE63dzc3nzzzTfffPOVV15h2by2b9+u5UAJzfbx8dm5c6d4R7Kzs319fdu1a9epU6eZM2c+ePCgtLR0xYoVbEMzZ868dOlSnS8Qj/6NLx4cE73g+JoG/YR64Thu//79+rof0KtXL9bnWy+1SVJTOERKpfK111773//+Z4gRRr788kt/f3+pvgf0+3mRBhwTvcD1Rgnianfjxg1Tt04i5HL5/PnzMVwWQNOB/o1NTuNzU0n1d73AhOm7MjMzZ86cqVQq1Wr19evXjbx1ANAC52dNSGlp6YcffijkpsrIyDB1i5ockx8iKyur4uJiMzOzPXv2WFhYGHnrLxSO42QyWXh4+Nq1a8UPF968eVNIA52Xl5eSkuLv71/fDAlXr1595513OnToYGdnFxAQwDoHMUlJSf369WvTpk3fvn1TUlLEayUnJ0+aNCkqKiokJEQYhlutVkdERLDHWoQWrl27dsGCBeyiSH13HBrOpHfvJIJwLxf0ytD9QXJyckxYiY6fFyJ6+eWXqxSeOXNmypQpFRUVQol4xDUdXb16dfz48V999dWlS5eCgoKIaOTIkWxWREREYGCgXC5fuHAhu5gcHx/PZq1YscLZ2fnx48c8zz9+/NjZ2TkuLo7NevTo0YQJE7KysqpsiI1CoEuT8B2iF4hneoD3IuiXQePZH3/84eHhYcJKdI9nVaLU1atXnZycxF1Ma1tSu7i4OKVSyf5ng3O2bt2a5/mcnJypU6cKi504cUKIqXfu3DE3N1+zZo0wNzo6ulWrVoWFhWzyypUr7u7uVUbmrDL6mhb4DtELXG8EeIGwvDkPHjwweSX1xfN8YGDge++9165du0ZWtWDBAnFHnsrKyvfff5+Ibt++LVzJJCIvLy87O7uCggIi2rVrl0qlGjlypDDX09NTqVQmJSWxyVdffdXV1bVJJc5+ASGeATRXtWXn0T1vjr6S79QrGVDDHDly5OLFi2y4Fj366KOPYmNj2QOOQ4YMYSO0CSoqKjw8PIjo+++/J6IuXboIs9j4aleuXBFKvL29t2zZkpWVpd8WQj2Y+gRRCgjXCkCvdLneqD07jy55c/SYfKfOZEBiOn5eqmwiICCA4ziVSlXnkjr66quv2AhtLi4uW7durb7A+fPnW7ZsefHiRZ7n+/btS0RlZWXCXDaQzaBBg4SSS5cuEZH4miSuNxoZzs8AmqWYmBiFQsFG+SIiOzu7qKiorKys1atXE5G5ubl44SqTjJmZ2dixY9l5RkxMjIeHR0BAwMqVK4koPj5ex0oYX1/f4uJiHx+fxu5V7dLT062trVnuPb0YMWLE5s2bExIS7t+/P2PGDJaRVaBWq5ctW5acnNyvXz8iatu2Lf0554N4pFCGndt99913+moh1BfiGUCzVGd2Hh1VT75DRA1IvlOvZEANcO/evfom3NHOxsamV69e//jHP7744gsiYrn6BJ9++unIkSMnT57MJtmZljix+OPHj+l5bgehQiISshqB8SGeATRLQnYeoUQv2Xn0nnxHX2QymYHyM7CRPMVPEx49etTKymr58uVCCUuBxEbiZtgja0OHDhVK8KiZySGeATRL2rPzNDhvToOT7xgo2AgcHBzEp0d6xCLTmDFj2OTJkydzc3PDw8OFBdLT04OCgmxsbE6fPi0UpqWlWVhYTJkyRShhZ2ydOnUyRCNBF4hnAM2S9uw89U0t1MjkO3UmA2q84cOHl5SUsPxEYmVlZVQtmm7YsKF379779u2rsapNmzYlJyez8FxeXh4eHu7v78+O26lTp2JiYtRqtVwul8vlCQkJixcvPn78uK2tbWRk5ObNm1kDSkpKEhMTo6KixD0eCwsL6c9nbGBkGL8RoFlq2bJlenr6ypUr33333T59+shksvbt26elpbEeE2vXrs3Ly9u4cWNmZmZCQsLhw4ednZ2LiooqKyv9/Py2bdt24cIF8UXF2NjYadOmaTSa/Pz8s2fP1rcSS0vLtm3bsmw7BhIcHJyUlJSenj569Gih8MyZM2zcqezs7M8++8zLy+u1114joqysrOvXr3/wwQfCDTCx4uLizz//nM21sLCYN28ee7AsPT3d19dXqVSmpaUJC3Mcd+vWLSIKCwvr0KHD3LlznZycFArF0qVLQ0JCxNWeP39eJpNhjHxTMnUHSykg9LUFvTJm/jPd+5Tri46fF6rWC3/MmDGLFi3ScSs3btwYMGBAQ9rXUG+//XZISIi4BP31jQzXGwGgiWJXOAUpKSnHjx/XpQOhUqmMj4/funWrwZpWVWZmpkKhEA8vQn9Opw5GgOuNAC80EybfqdMff/yxcOFCR0fHCRMm9OjRo2PHjocOHQoNDd26davwgEGN2HN44ocZDCo/Pz86Ojo1NZVt8ebNm4cPH3706NHvv/9unAYAg3gG8IIqLS1dvXq1kHwnJCRk4MCBpm7U/+FrSuPn7u4eHR0tl8u1j5To7u5usHZVVVlZuWPHjt27dwvhs0ePHqx75Nq1a43WDCDEM4AXlpWVVXR0dHR0tKkbUj8uLi5NatjfFi1aiDv3gwnh/hkAAEgB4hkAAEgB4hkAAEgB4hkAAEgB+oPoR3p6uqmbANLB3k5ffvmlqRtiKPi8gCFwNXaKhXrBuNoA0Ej79+/HWFmNhHgGYHAcx+HbCsDQcP8MAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkAPEMAACkgON53tRtAJCaWbNm3bhxQ5i8ePGii4uLra0tm5TJZNu3b+/SpYuJWgcgTS1M3QAACbK3t09MTBSX/O9//xP+7969O4IZgN7heiOA/k2ZMqW2WRYWFtOmTTNiWwBeFLjeCGAQ7u7uV69erfHzdePGjZ49exq/SQDShvMzAIMIDg6WyWRVCjmOe+211xDMAAwB8QzAIAICAtRqdZVCmUz27rvvmqQ9AJKH640AhjJ48ODMzEyNRiOUcByXk5PTuXNnE7YKQKpwfgZgKEFBQRzHCZNmZmZDhw5FMAMwEMQzAEPx8/MTT3IcFxwcbKrGAEge4hmAoXTo0GHkyJFCrxCO48aPH2/aJgFIGOIZgAEFBgayW9Qymczb27t9+/ambhGAZCGeARjQhAkTLCwsiIjn+cDAQFM3B0DKEM8ADMjKysrHx4eILCws3n77bVM3B0DKEM8ADGvq1KlENH78eCsrK1O3BUDSeAnZv3+/qQ8nAECzMXHiRFN/beuTBMfXR1SDpmbXrl2TJ09u0aIZfNw2bdpERKGhoaZuiP6lp6fHxsbi+0HAXmspaQYfsPqaNGmSqZsA8Ce+vr4vvfSSqVuhkwMHDpB0P0SxsbFS3bUGYK+1lOD+GYDBNZdgBtCsIZ4BAIAUIJ4BAIAUIJ4BAIAUIJ4BAIAUIJ4BAIAUIJ4BQGMNHDgwLCzM1K0wrJs3b27YsIH9n5eXl5KS4u/vP3jw4HpVcvXq1XfeeadDhw52dnYBAQH5+fnCrKSkpH79+rVp06Zv374pKSnitZKTkydNmhQVFRUSErJ3715WqFarIyIi7t6927jdkhQJPn8GAEbm4uJi0GcScnNzu3TpYrj663T27NnExMRt27axSUdHx1GjRk2fPt3NzU33Sq5duxYVFTVt2rRPPvlk48aNO3fufPDgQWpqKhFFRkbm5uaGhIQoFIrExMTp06eXlpbOmzePiFauXJmcnHzp0iUbG5uioqJ+/fo9ePBgwYIFMpksPDx8xowZ69evd3FxMcBON0OmHqBEn9iT/6ZuBUAzNnHixKY2BtIff/zh4eHR+Hoa/P1w9epVJyenhw8fViknIjc3N93riYuLUyqV7H+VSmVjY9O6dWue53NycqZOnSosduLECSJ6+eWXeZ6/c+eOubn5mjVrhLnR0dGtWrUqLCxkk1euXHF3d3/69GkD9qsJvtaNhOuNANB03b1718fH58GDB6ZqAM/zgYGB7733Xrt27RpZ1YIFC1q2bClMVlZWvv/++0R0+/Zt4UomEXl5ednZ2RUUFBDRrl27VCrVyJEjhbmenp5KpTIpKYlNvvrqq66urkuXLm1k26QB8QwAGk6j0Rw4cGDatGnDhw8noiNHjsyaNatr165FRUXTpk3r0KFDnz59fv75ZyLKyMj44IMPXFxc7t+/P3HixPbt2/fp0+fw4cNEtGXLFjMzM47jiKikpGTjxo3C5LZt23777bd79+7NmTOHbfH06dNdu3Y9d+6ccXbwyJEjFy9efOutt/Rb7UcffRQbGxsbG0tEQ4YMsbe3F8+tqKjw8PAgou+//56IxNdau3btSkRXrlwRSry9vbds2ZKVlaXfFjZLpj5B1CdcbwRopAZcg7pz5w49v/KWm5vbunVrIoqOjr59+/auXbuIaMCAAWq1+ujRo+zsZP78+efOnduzZ0+bNm2I6Pz58zzPu7q6ij+84kn682W9//znP61atfr666/ru2sN+34ICAjgOE6lUlWfRfW83sh89dVXw4YNIyIXF5etW7dWX+D8+fMtW7a8ePEiz/N9+/YlorKyMmGuUqkkokGDBgklly5dIiLxNUkd4XojAMCfsDMGpnPnzp07dyaiZcuWOTk5TZ061d7e/vLly2ZmZmPHjmVLxsTEeHh4BAQErFy5koji4+OJyNzcXFxnlUkxX1/f4uJiliXVCNLT062trfWYG2HEiBGbN29OSEi4f//+jBkztm/fLp6rVquXLVuWnJzcr18/Imrbti0RsVNVhv1fUVEhlLBzu++++05fLWy+EM8AQJ/EX75EZGtrW15ezv43MzMjolatWrFJX19fIrp582Z9NyGTyRrbSp3du3fP1tZWjxXa2Nj06tXrH//4xxdffEFEO3bsEM/99NNPR44cOXnyZDbJ+k8WFRUJCzx+/JiIHB0dxRUS0f379/XYyGYK8QwATIN9KYtP75ogmUymVqsNUfO4ceOIyMLCQig5evSolZXV8uXLhZLevXsTUV5enlDCHlkbOnSoUFLlB8SLDPEMAEzj4cOHRDRq1Cj682U0nuefPHkiLMZxXGVlpXhFAwWYGjk4OIhPj/SIRaYxY8awyZMnT+bm5oaHhwsLpKenBwUF2djYnD59WihMS0uzsLCYMmWKUMLO2Dp16mSIRjYviGcA0ChPnz4louLiYjb57Nkz8dySkhIiEgckIRqlpqb2799/1qxZ9PzC2qpVq27duhUXF8cuUZ44cUKj0bi6uubn5+fk5LC1jh07ZmNj88033xh6v5jhw4eXlJSwfRQrKyujapF1w4YNvXv33rdvX41Vbdq0KTk5mYXq8vLy8PBwf39/9tD0qVOnYmJi1Gq1XC6Xy+UJCQmLFy8+fvy4ra1tZGTk5s2bWQNKSkoSExOjoqLEPR4LCwvpz2dsLyyMDwIADadUKlevXk1EeXl5mzZtqqioyM7OJqLo6Oj58+enpKSwAZmWL1/+8ccfs1ViY2OnTZum0Wjy8/PPnj3LulqsXbs2Ly9v48aNmZmZCQkJhw8fdnZ2Lioqqqys9PPz27Zt24ULF9iVSUtLy7Zt21paWhpnB4ODg5OSktLT00ePHi0Unjlzho07lZ2d/dlnn3l5eb322mtElJWVdf369Q8++EC4ASZWXFz8+eefs7kWFhbz5s1jD5alp6f7+voqlcq0tDRhYY7jbt26RURhYWEdOnSYO3euk5OTQqFYulkn57AAACAASURBVHRpSEiIuNrz58/LZDLk3SYijud5U7dBb7788kt/f38p7RGAkfn5+RHRgQMHDFF5r169rl+/bqpPaIO/H8aOHduzZ89NmzbpsrBCoQgODs7IyKh/AxvI19e3U6dOiYmJ9V3RoK+1SeB6IwCANikpKcePH9elA6FSqYyPj9+6dasRWsVkZmYqFArx8CIvMsQzoxLuMUAzgldNX0pLS4W/zUjHjh0PHToUGhrKnmXWIisra/Xq1e7u7sZpWH5+fnR0dGpqKnsyHRDPjGT9+vXDhw9v3759w1aPj4+PiIjw9PQcNmyYQqHQb9uMQ0s6DO2Sk5Pd3d379u3bpUsXjuM4jjtz5ozBmvknWl619evX29rachzXokULb2/vt99+28fHZ9SoUd26deM4Tui8AExpaemHH37IDsuCBQuMeTlOL9zd3aOjo+VyeZ2LGS20VFZW7tixY/fu3abNPNC0mHR0Ej1ryuNdPXv2jH0tNmDduLi41q1bV1ZWFhUVTZgw4ccff6xvDTk5OQ3Yrh5FREQEBgbK5fKFCxeyQY/i4+N1WTE5OZmI9u3bxya/+uora2vrnTt3GrKx/0f7q8aeCurRo4e4UKPR+Pj4/P777w3YnMlfJl6KYyAJmvL3g0lI77XG+ZmRWFpa2tnZNWzdf/3rX507d5bJZNbW1ocOHXr99dfrtXp2drb4aRXjy83NzcnJ2blz59y5c2NjY//9738TUVxcnC7rstET/t//+39s8p133klMTMzNzTVca8W0v2oODg5UbawKjuMiIyPZGIb1YvKXCaC5QzxrBnJycho8BIDJ022Q1nQYddJoNEQk7lr297//vV5JFI3sypUrgwcP7tixY73WagovE0Bz9yLGs59++mngwIHz5s376KOPzM3NS0tLtWSyIKJnz56tW7duxowZr7/++ujRo3/99Vft5aWlpatWrQoKClq4cOGIESOqnIg8ePCAbcLd3f2nn37S3tRjx47NmTOntLSU5ctg/9e23Zs3b/r5+UVERAQHBw8bNuyXX36hauk2akvModFozp49Gxoa6uLikpeXN2LEiG7duhUVFdW2rerHUMteaEmHQXWl/5g/fz4RffLJJ+PGjWMdzGQy2TvvvENa84+Y5FVTqVS//vora7CWDTXZlwmg2TP1BU990vH6eM+ePdu1a8f+9/f3v3fvnvZMFiEhIeyhGZ7nvby87O3ti4uLaytXqVQjRowICgrSaDQ8z7OODyy3BTur+Pjjj7Ozs48dO0Z/TvqgBf05LUVt7enRo4erqyv/PPWtu7t7javXmJijvLz8hx9+YAPFrlmzJjU1dcaMGU+fPq1tW1WOYUFBgS47wojTYfA6pP/YuXMnG3G1Xbt2mzdvVqvVPM/XmX/EOK9a9Q+UjY1Ns36ZpHdPRYD7Z1VI77V+EZ+n7tix44MHD+Li4ubPn88yqbdp0+aVV15RKBSlpaXsyyIuLm7RokWTJ08ODQ0dMGBAlRqOHj1qZ2dXY7lCoVi8ePGNGzd69uxJRGq1eufOne+88w4bVPv69esajYb97u7QoUNZWZkuP5k5jnNzc7t27RoR/fjjjzVud+zYsZs2bXJwcJg8eTLP8z169Lhz5w4bDU+8OlV7plU86ebmduPGjUePHrEBxbVsq8ZjWOeOsAMycuTI2bNniwdQUKvV2kdMf/jw4UcfffTFF1+o1WofH599+/ZZWVkRkclfNfGx1Wg0WVlZEydOvHz5cvN9mfz8/HJzc0NDQ7Uv1hylp6fHxsayqAZEtGnTpi5dukjpeWpJ/VrR8ffXwYMH2af6b3/7W0ZGBitkP8OFZViy1/79+yckJAi/oMVqK2cpMEpLS6vPqrKJKpNakOiXe23bZZ4+fSqXy1euXMm68FZfXXszqszSsq0aj6Euli9fvmLFCt2XF7t8+bKTkxMRzZ07t8YGG/9Vo2oZHRMTE7VsiGnKL9PEiRON9NUDTYDEzs9exPtnf//73y9fvuzt7f3TTz95eHhUyafHCJksHj58mJWVVeU5So1GU1s5u8fTgJROOqptu0R04cKFPn36dO/ePSoqqgH96+q1LV2OYXXV02Fod+7cOZZ7l3nttdfOnDnDcVxt4702hVeNja3XrF8miX3HCXC9sQrp/XZ5EePZxx9/3L1792+++Wbv3r0qlSoqKqr6MkImCzc3N6VSuXbtWmHWtWvXEhISaitnw5JGR0fzz68U3b59+7///a++Gl/bdokoODhYpVK99dZb9PzrjKmSbkNLYg7dt6XLMayixnQY7J/a0n+0adNm8eLF4n1xcXGxt7evrfdg03nVmu/LBNCMmfYHgn7p+PurVatWjx8/5nlepVJZW1sPGDCAf34Np7Kyki2zffv2/v37q1SqZ8+ede/enYimT5++e/fuqKgoLy+v4uLi2sqzsrLYrR1PT0+5XL58+fJZs2axXgbs7IHdqOd5nj299PTpU+2tffToERF1796dTda2XZ7nra2tOY779ttvd+/ezb7xMzMzc3JyXn75ZSsrqzt37rAaxo8fT0TLly+/efPmpk2b2rVrR0TffPONWq12dnYWN0nLtmo8hlqkpqZ6enomPBcfHx8aGhoVFcXz/NGjR1u3bv3f//63+los1ci0adNKSkpYyddff01EycnJbNK0rxpL4eHk5FS95c30ZeKl2EdAgPOzKqT3Wkvq1dXx/UpEf/3rX2NiYqZOnerj4/PHH3/wz78Z169fX1hYWFBQEBMTI3xfZGdn+/r6tmvXrlOnTjNnznzw4IH28l9++cXb29vW1rZz586LFi168uSJRqP57LPP2A+IRYsWPX36dN26dWxyyZIl5eXltTX1l19+mT17NhGZmZl9+umnV65c0bJduVxubW39xhtvZGRkxMXF2drajhs37uHDh5GRkQ4ODocOHWKLKRSKAQMGWFlZeXl5KRQKDw+PoKCg5ORk4cf7zJkzL126pH0fazyGtRG65IlxHMcG0Th58qSjo2NaWlqN67L40b59+9GjR48ePXrw4MFfffWVMNeEr9qZM2fef/99NhkRESF01xQ0u5eJkd53nADxrArpvdYvYv/GGpk2kwU0DF41vZNeDhEB8klVIb3X+kW8f9bUcLW7ceOGqVunK2nsBQA0X8hP/f8TMlmw+yjGJI0fjCbZCxO+agDQ1OD8rNlnsngx4VUDgCoQz8jKyop11OZ5PikpaeDAgaZuEdQNrxoY2s2bN4VxtPPy8lJSUvz9/QcPHlyvShq8opZ8gcnJyZMmTYqKigoJCdm7dy8rVKvVERERd+/erddWJAbXGwHAeHJzcxuff1IvlWh39uzZxMTEbdu2sUlHR8dRo0ZNnz69vrkdGrZiZGRkbm5uSEiIQqFITEycPn16aWnpvHnziGjlypXJycmXLl2ysbEpKirq16/fgwcPFixYIJPJwsPDZ8yYsX79ehcXl3o1UjJwfgYARqKXHG9GSBR37dq14ODg+Ph4c3NzobBr164Nq62+K2rJF5iTk7Ny5cpZs2axEbptbGxCQkIiIyPZSAK2trYff/yxr6/vC5tIAfEMAIxBLznejJAojuf5wMDA9957jz3Dbnxa8gXu2rVLpVKNHDlSmOvp6alUKpOSktjkq6++6urqunTpUiO3uYlAPAOAeisuLg4PD4+MjFyyZIm3t/eSJUuKioqo9sxtVC3Hm5b0dbpXQnXlz2uAI0eOXLx4kQ1IZhJa8gV+//33RCS+1spO/q5cuSKUeHt7b9myhY3N/cIx/iPchoPn/wEaSZcxI0pKSnr27PnJJ5+wyYKCgp49e3bv3r2oqIivJXMb+5+e5xCoM32dLpUwdebPE+j4/RAQEMBxnEqlqj6LqqVT0FGDV+T/nC+wb9++RFRWVibMZeNQi3PysSG816xZU2fN0hsfBOdnAFA/MTExCoVi1qxZbNLOzi4qKiorK2v16tVEJL7nVH2SMTMzGzt2LDu3iImJ8fDwCAgIWLlyJRHFx8frWAnj6+tbXFzs4+PT2L16Lj093draukWLJtFXTq1WL1u2LDk5uV+/fkTUtm1bej5WNSMet5ph53bfffedsdvaBCCeAUD9nD9/nojEqUGHDRtGRD/88EO96jEzMyMiYWxPloWuAVl7tCeDra979+6xRKlNwaeffjpy5Egh+S3rJMku7TKPHz+m55mSGNZVhKVAetEgngFA/bA4lJ2dLZSwcwJra+vGVCukr2tU4xpNJpPVlsDIyKrnC+zduzcR5eXlCSX5+flENHToUKFEfPb2okE8A4D6YWdjx44dE0rYQC2jRo0irZnbquR4q0JIX1ffSvQbfhwcHMQnQKZSY77AoKAgGxub06dPC4VpaWkWFhbiBxjYGVunTp2M2domAvEMAOonLCzM3d09Pj7+3r17rEQulw8ZMoQ98Muuia1aterWrVtxcXHl5eVEdOLECY1G4+rqmp+fz4KfQIhGqamp/fv3Z7fldK/k2LFjNjY233zzjb72bvjw4SUlJSy5nVhZWRlVi50bNmzo3bt3bQnTG7ziqVOnYmJi1Gq1XC6Xy+UJCQmLFy8+fvy4ra1tZGTk5s2bWfNKSkoSExOjoqLEPR4LCwvpz2dsL44mcc8TAJqRli1bpqenr1y58t133+3Tp49MJmvfvn1aWhrrQ7F27dq8vLyNGzdmZmYmJCQcPnzY2dm5qKiosrLSz89v27ZtFy5cEF9UjI2NnTZtmkajyc/PP3v2bH0rsbS0bNu2raWlpb72Ljg4OCkpKT09ffTo0ULhmTNn2MhS2dnZn332mZeXF8tpnpWVdf369Q8++EC4xVVFA1ZMT0/39fVVKpVpaWlCIcdxt27dIqKwsLAOHTrMnTvXyclJoVAsXbo0JCREvPr58+dlMtmkSZP0cjSaF+Q/A4D/Y8ycWEZOX6f798PYsWN79uy5adMmXapVKBTBwcENGBG7wStq5+vr26lTp8TExDqXRP4zAACJS0lJOX78uC5dBJVKZXx8/NatW+u7iQavqF1mZqZCoRAPL/JCQTwDANMQ0teZuiFVdezY8dChQ6GhoexpZS3YU3fu7u713USDV9QiPz8/Ojo6NTVV/CjFCwXxDACMremnr3N3d4+OjpbL5XUu1rDg0eAVa1NZWbljx47du3cbOvNAU4b+IABgbCx9XXR0tKkboo2Li0szGti3RYsW4s79LyacnwEAgBQgngEAgBQgngEAgBQgngEAgBRIsD8Ie0gQABqAdTWU5IcoNzeXJLprDZORkTFw4EBTt0KfJDU+SHp6+saNG03dCoCq/vvf//br1+/FHCIWmrJBgwYtXrzY1K3QG0nFM4CmieO4/fv3v5hD6gEYDe6fAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFCCeAQCAFLQwdQMAJKioqIjneXFJaWnp48ePhcnWrVubm5sbvV0AUsZV+dQBQON5enqePn26trkymezu3bv29vbGbBKA5OF6I4D+BQQEcBxX4ywzM7Nhw4YhmAHoHeIZgP5NnDixRYuaL+ZzHBccHGzk9gC8CBDPAPTP1tbWy8tLJpNVn2VmZjZ+/HjjNwlA8hDPAAwiMDBQo9FUKWzRosXYsWOtra1N0iQAaUM8AzAIX19fS0vLKoVqtTowMNAk7QGQPMQzAINo1arV+PHjq3TKb9my5ZgxY0zVJABpQzwDMJQpU6aoVCph0tzcfOLEiS1btjRhkwAkDPEMwFC8vb3Ft8pUKtWUKVNM2B4AaUM8AzAUc3PzyZMnW1hYsEkbG5uRI0eatkkAEoZ4BmBAAQEBFRUVRGRubh4YGFjbQ2kA0HgY7wrAgDQajaOj4/3794no+++/HzJkiKlbBCBZOD8DMCAzM7OgoCAicnBwGDx4sKmbAyBlf7r6kZub+8MPP5iqKQCS1KFDByIaMGDAgQMHTN0WAEnp2rXroEGD/m+aF9m/f7/pGgYAAFAPEydOFIewGu5O444agH4dPHhw4sSJpm5Fc/Lll1/6+/tL9buI47j9+/dPmjTJ1A1p3vz8/KqU4P4ZgMEhmAEYAeIZAABIAeIZAABIAeIZAABIAeIZAABIAeIZAABIAeIZAABIAeIZAEjHwIEDw8LCTN0K47l58+aGDRvY/3l5eSkpKf7+/vUdWa3BKyYlJfXr169NmzZ9+/ZNSUkRz0pOTp40aVJUVFRISMjevXtZoVqtjoiIuHv3br22ojuM9g0A0uHi4vLSSy8Zrv7c3NwuXboYrv56OXv2bGJi4rZt29iko6PjqFGjpk+f7ubmVq96GrZiZGRkbm5uSEiIQqFITEycPn16aWnpvHnziGjlypXJycmXLl2ysbEpKirq16/fgwcPFixYIJPJwsPDZ8yYsX79ehcXl3o1UifVx7viAQBMqml+F/3xxx8eHh6Nr4eI9u/f38hKrl696uTk9PDhw+qVu7m5NaxVuq+Yk5MzdepUYfLEiRNE9PLLL/M8f+fOHXNz8zVr1ghzo6OjW7VqVVhYyCavXLni7u7+9OnTBjRSbOLEiVXGu8L1RgCAut29e9fHx+fBgwembggREc/zgYGB7733Xrt27UzSgNu3bwvXOYnIy8vLzs6uoKCAiHbt2qVSqcSpaz09PZVKZVJSEpt89dVXXV1dly5dqvdWIZ4BgBRoNJoDBw5MmzZt+PDhRHTkyJFZs2Z17dq1qKho2rRpHTp06NOnz88//0xEGRkZH3zwgYuLy/379ydOnNi+ffs+ffocPnyYiLZs2WJmZsZxHBGVlJRs3LhRmNy2bdtvv/127969OXPmsC2ePn26a9eu586dM/7OHjly5OLFi2+99ZbxN80MGTLE3t5eXFJRUeHh4UFE33//PRGJr8p27dqViK5cuSKUeHt7b9myJSsrS8/NEp+sNc1zfAB40TTsu+jOnTv0/KJZbm5u69atiSg6Ovr27du7du0iogEDBqjV6qNHj7Zs2ZKI5s+ff+7cuT179rRp04aIzp8/z/O8q6ureNPiSfrzFbn//Oc/rVq1+vrrr+vbTmr09caAgACO41QqVY2VG+F6YxXnz59v2bLlxYsXeZ7v27cvEZWVlQlzlUolEQ0aNEgouXTpEhGJr0k2AK43AoBksfMApnPnzp07dyaiZcuWOTk5TZ061d7e/vLly2ZmZmPHjmVLxsTEeHh4BAQErFy5koji4+OJyNzcXFxnlUkxX1/f4uJiHx8fA+2OFunp6dbW1i1aNIkOfWq1etmyZcnJyf369SOitm3bEhE7qWXY/xUVFUIJO7f77rvv9NsSxDMAkCbxVyoR2dralpeXs//NzMyIqFWrVmzS19eXiG7evFnfTchkssa2skHu3btna2trkk1X9+mnn44cOXLy5MlsknWSLCoqEhZ4/PgxETk6OgolNjY2RHT//n39tgTxDABedOyrVnx618TJZDK1Wm3qVhARHT161MrKavny5UJJ7969iSgvL08oyc/PJ6KhQ4cKJVV+augL4hkAvOgePnxIRKNGjaI/Xxzjef7JkyfCYhzHVVZWilc0VVBxcHAQnwCZysmTJ3Nzc8PDw4WS9PT0oKAgGxub06dPC4VpaWkWFhZTpkwRStgZW6dOnfTbHsQzAJCIp0+fElFxcTGbfPbsmXhuSUkJEYkDkhCNUlNT+/fvP2vWLHp+uWzVqlW3bt2Ki4tjlyhPnDih0WhcXV3z8/NzcnLYWseOHbOxsfnmm28MvV/VDR8+vKSkhO2vWFlZGVWLshs2bOjdu/e+ffu0VNiAFU+dOhUTE6NWq+VyuVwuT0hIWLx48fHjx21tbSMjIzdv3syaV1JSkpiYGBUVJe7xWFhYSH8+Y9MPcecQ9G8EgKagAd9FpaWlkZGR7Gtt48aNMTEx7P9Vq1Y9efIkNjaWTUZERJSVlbGgtX79+sLCwoKCgpiYGOHxXoVCMWDAACsrKy8vL4VC4eHhERQUtG/fvvLy8sjISAcHh0OHDrElT5486ejomJaWVt+9o0b3bzx79iwRffvtt+LC06dPz5w5k4jMzc3XrVt3+fJlVj537lwzM7POnTvXVlsDVvzhhx+Eu48CjuN+//13tkBSUlJQUNCHH37o5+eXmJhYZfV//etfMplMWLhhqvdv5HieF1rz5Zdf+vv7i0sAAIzP0N9FvXr1un79uqm+6ziO279//6RJkxpTydixY3v27Llp0yZdFlYoFMHBwRkZGfXdSoNX1M7X17dTp06JiYmNqcTPz4+IDhw4IJTgeiMAQPOTkpJy/PhxXboIKpXK+Pj4rVu31ncTDV5Ru8zMTIVCIR5eRF+afTwrKCg4cODA6tWrTd2Qpkt8QxtMCO/VpqO0tFT420x17Njx0KFDoaGh7GllLbKyslavXu3u7l7fTTR4RS3y8/Ojo6NTU1PZM+z6pbd4Fh8fHxER4enpOWzYMIVCoa9qtbt+/fqKFSsmTZq0c+dO42yxRuvXr7e1teU4rkWLFt7e3m+//baPj8+oUaO6devGcZxw99jIysvLV69ePXjw4Pbt2xNRamrqmDFjOI7jOM7T09PT0/P1118fN25cUlKS+DlHxphJN7SknKjN6dOnOY6ztrZ+7bXXBg4cyHFcy5YtBw4c2KdPn5YtW3Icp/fnWnSh/W1w8uRJA71XCwoK5s+fP378eD8/v4kTJy5cuFDHMQbPnDkzadIk9paYPXv2Dz/8oN+GNU2lpaUffvgh+1QuWLBA71fSjMnd3T06Oloul9e5WMOCR4NXrE1lZeWOHTt2795tqBwF4ptput+DzcnJEU/GxcW1bt26srKyqKhowoQJP/74Y2Pu8tUL68LU4GFa9IU9bNGjRw9xoUaj8fHxaeQ9z8YoKytjw5WySZZ2yMXFRWje119/7erq2qNHj99++0284uTJk5cvX26EFkZERAQGBsrl8oULF7IhiOLj4+tc69ixY2+++WZpaSmbFL8BHj582KNHj6ysLAM2unba3waGeK+eOXOmU6dO69at02g0PM+r1epNmzZ17tz53LlzuqzOftp369ZNj03SC2n3TSN9jK8P1fuDNCSeVU+a4Obm9sorr+iliQ3QFOJZbc04f/78/fv3TdIehvXjEiarNzIvL8/BwcHV1VU83ppxaEk5od3Bgwf/+9//CpNVdmrjxo1VwrMxaX8b6Pe9WlJS4ujo+Pbbb1cpnz59eseOHZ88eaJLJU3k41MF4hnUSQ/jN9aYNCEnJ8dAz3s3a9evX+/Xr1/Hjh1N3RBtHBwcVq5c+fvvvxvi9qx2WlJOaDdmzJjRo0fXNnfu3Lk9evTQTxP14cqVK4MHDzbE22DdunV5eXnV827MmDGjoKBg/fr1et8iQFNW73hWJWnCsWPH5syZU1paykrY/1pWLy4uDg8Pj4yMXLJkibe395IlS9hT7loyONTLzZs3/fz8IiIigoODhw0b9ssvvxDR7t27raysOI5bu3Yte2Bwz549lpaW27dvJ6Jnz56tW7duxowZr7/++ujRo3/99VeNRnP27NnQ0FAXF5e8vLwRI0Z069atXk/j8zzP7mqwRzv/97//eXl5cRzn6+v76NGjsLAwJycndh9F+47XuDtaEmEQUVlZ2ZIlS2bNmrV8+fJly5bpcsd74sSJMpns22+/pWpJN5RK5e7du6dMmTJkyJCMjIy//vWvzs7O58+fVygU48ePt7Oz69Wrl7BpIvrpp58GDhw4b968jz76yNzcXPvWtaScIK3JOFq2bKll3DxLS0tzc/PqL2udh67Gxtf4jtXxHaJSqX799df58+fX2M7aPgunT5+2tLRs06bNd9999+TJk6CgII7j3nzzzd9++42ILl265OjoyDo6s4PDBoEV69WrFxGdOXOGGv3JaiIfKACdiE/WdDzHp2oXKKqX1KikpKRnz56ffPIJmywoKOjZs2f37t0fPXqkPYOD7u3p0aOHq6srz/MqlcrGxsbd3Z2VR0VFEZFwGerOnTvjx49n/4eEhLAnUXie9/Lysre3LywsFJ4WXLNmTWpq6owZM+rMplrj4b137x6bW1pa+pe//MXFxaW8vNzX11ehUPA8X2fqihp3p7ZEGDzPV1ZWDhgwICQkhG30999/ZyNw13isxBwcHNq3by8cHGExjUZz69YtIrK2tj527NjVq1eJyNnZ+bPPPnvy5AlL+jBixAihnp49e7Zr14797+/vX1BQoP2giYlTTvD1ScZR405Vf1mLi4u1HLoaG1/bO7agoKC2d0j194CNjU31ptZWc1FREc/zc+fOfemll9gFw7KyMnt7+8DAQLZkZWXlsGHD2P92dnYdO3as8Zh06NChY8eOdb7Bajt6AlN9oHC9Eeqkn+epOY5zc3O7du2alpIaRUVFRUdH5+fnC8N27dy5Mzg4OCwsbO3ata+88opCoSgtLWXv+7i4uEWLFk2ePHnv3r26t2fTpk0ODg6TJ0/meb5Hjx537txhnfcePXrk7Ow8efJk9sM2JiamT58+Y8eO/fHHHwcMGFClwqNHj44dO9bNze3GjRuPHj3ScRxrcTN4ni8oKPDz8ztw4IBwCvLzzz8PHDjw9ddfnzlz5rRp04QVtex4bbvD2ia8Up06dSoqKnr27JlcLp83b961a9fYbTOhcmHJ2l4pJycntVrNOoxUX0w82aVLl7t37woV2tvbV1RUsNHYiKhjx44PHjyIi4ubP38+ywevY/8otVo9cuTI2bNnC6N0s0Jdxi+vvlN1vqzVD12NjV+7dq2Wd2yN7xBxYzQaTVZW1sSJEy9fvlxlrvbPjIUWVwAAIABJREFUwrVr1/7yl798/vnn7CrIuHHj0tLS8vPzW7du/fXXX+fn57PRHOzs7MzMzGrszNm1a9eysjI2qpD2T5b2D6+pPlDsu2jixIl1LtkcHTx4cODAgYbq4/fCyMjIGDhwoMmepz5//jwRib/ghg0bRkSso7BeMjiEhoa+/fbbn3/+eXR0dHl5uUqlYuXt2rWbP3/+9u3bWQ+0U6dOsdSuFy5cEH5yCsaOHUvPhyVtWFIGjuPs7e1DQ0PFyZP69+8fHh6emZlZ5QKRlh2vbXdqS4TBrhk6OztXqVw7lUp1//59loWvTlXiU7t27cQXjv71r3+1adNm4cKFb7zxxtOnT3Xv7Fsl5QTT4GQcdb6sAnEOkeqN1/6OrfMdYmZm9vLLL//jH/+oPkt7zb169fL09Pziiy+I6Pbt22q1uqKigoWfHTt2BAYGslV69epVUFBQ/fnCysrK+/fvC48NNeaT1UQ+UAA6Eb/tDH290dPTk4h+/fVXoYQNgjl27Fi+Wk889pP5nXfeqVd7fvzxRxcXF9b5rUqFhYWFrVu3Xrp06U8//bRs2TJW+Omnn7Zq1Uro+c2o1erqq9erGWIlJSWsQo1GM3ny5G7duvXp06e8vFxYQMuO17Y7VVYRJvv3709Eubm5tVVeYyPZgKobNmyobTHxZG2bFvz+++/e3t5EZG5uvm3btlqO1p98/fXXMTExuixZo+o7pfvLWmWySuPr9Y6trTE1ztVeM8/z7BbXjz/+OGfOnN9++23y5Mmvv/76b7/99sEHHwirsCQd6enpVbbCgqXwJtf+yaqtwQUFBSqVylQfKFxvhDrpJz919aQJOmK/QI8dOyaUsKcaWZqGKsQZHHQXHBysUqnYT0WNRiOe1b59+zlz5mzevPmf//zn9OnTWaGbm5tSqVy7dq2w2LVr1xISEuq1Ue2mTp3KfpmuW7duwoQJycnJv/7668cff1zb8uId17I7NWJfGeIjXKeKioply5b169dvwYIFuq9Vm48//rh79+7ffPPN3r17VSoVu8uiXY0pJ9g/DU7G0bCXtXrj6/WOrZc6a/b19e3atesnn3zC7rzOnj37woULc+fOZVcgmaVLl9rb2yclJVWp/PPPP3dwcBAfUjEdP1lz586VyWRN8AMFUCtxcNPxN9HLL79sZWV1584dNvno0SMi6t69e50rKpVKd3f3Ll265Ofns5KFCxcOGTJEpVLxz3++VVZWslnbt2/v378/m6W9TiJydnZmk9bW1hzHffvtt7t372Y9pDMzM4Wnv+/du2dpaSnuv/Ds2bPu3bsT0fTp03fv3h0VFeXl5VVcXMzzPLtqV2c3EKFmEj2qLFQeGho6adIknuczMjICAgJYOfumOHv2LJvUsuO17Q5rm7AhlldepVJdvny5RYsW7du3/+abb5RKZVpaGst9/scff1Q/VjzPX7x4cdiwYS4uLlevXhUKWVoNR0dHNsnOG4TnC11dXYmopKSETbKWsB/gPM+3atXq8ePHPM+rVCpra2uhq0VtUlNTPT09E56Lj48PDQ2Niorief7o0aOtW7cWP2dWI5aTwsnJqcqR1/6yVj90NTZe+zu2+jukxsYIxMdfe83MqlWrOI4TzuHc3NyqP2p29uxZR0fHhIQE9jy1RqPZtGlTx44dxYO+a3mDsauFnTt3ZqszT548mTlzJuuBYqoPFM7PoE76eZ5anDThl19+mT17NhGZmZl9+umnV65c0b5uSUlJWFiYl5fXkiVLwsLCVqxYIVx505LBoTZZWVnCWUVsbOzjx4/lcrm1tfUbb7yRkZERFxdna2s7bty4hw8fCqv4+Pjs3LlTXEl2dravr2+7du06deo0c+bMBw8elJaWrlixglU7c+bMS5cuaW/G6dOnx48fT0Qcx/Xq1cvb23vs2LFDhw5ld0cSExMPHTpkZ2c3Z84ctvyyZcuIyMbGJiUlRfuO17g7K1euZG2rMRHGuXPnhgwZ0qZNm+7du8fExAwbNmz27NmnTp06d+7c+++/z5YcMWKEt7e3r6/v3//+d7lcLj7OVZJu3Lp1a/HixURkaWmZmpp64sQJ1mFywYIFDx8+jI+PF049CwsLeZ4nor/+9a8xMTFTp0718fFhcbQ22lNO6JKM48SJE++99x5bcfbs2WfOnNHysrLjqeXQ1dj4Gt+xNb5DfvjhB+EIR0RECB01mervVS2fBaawsHDx4sXCZEpKSkZGRvWDcP/+/fnz50+YMMHPz8/Pz2/evHlVupXW9gZLS0sbN24ca5Kbm9ubb7755ptvvvLKK5aWlkS0ffv22t6Bhv5A8YhnoIMmnS/GCBkclErla6+99r///Y/1YG4iTJu6AiTPcG8ww32gpJ27Si/5YsAY+WK42t24ccO0Fcrl8vnz5zfss6f3/XpB4LhJWGM+UAB610LvNTb4J5WQwcHKykovFQoyMzNnzpypVCrVavX169cbVonhfirWtuPSINWf2M2I3t9gevlAAehdk8h/ZugMDlZWVsXFxWZmZnv27LGwsNBv5Y0hpdQV0AQZ6A3WZD9QknTz5k1hmNO8vLyUlBR/f//BgwfXq5IGr6glnVNycvKkSZOioqJCQkLqHPWizsao1eqIiAhhSIcGEt9Mk/Y9WABoLgz9XVQl45WRKyGd+4OcOXNmypQpFRUVQol4OLp6acCKWtI5rVixwtnZmfUHfvz4sbOzc1xcXCMb8+jRowkTJuie7Ek/z58BADRf2dnZU6ZMaQqVaHft2rXg4OD4+HjxMENdu3ZtWG31XTE3NzcnJ2fnzp1z586NjY3997//TURxcXFElJOTs3LlylmzZtnY2BCRjY1NSEhIZGQke7SxwY2xtbX9+OOPfX19G5w3HPEMAF4gNWa8Mkkl2vE8HxgY+N5777GUvManJZ3Trl27VCrVyJEjhbmenp5KpbL6o/319eqrr7q6ulZPgaQjxDMAaK5qy7mzZcsWMzMz9nBkSUnJxo0bhckqGa+05NPRvRLSmt6oYY4cOXLx4kU2MotJaEnn9P333xOReDxldr515cqVxm/X29t7y5YtWVlZDVlZfPER988AoCnQ5btIe84dNpCNsLB4kp7fuakzn44ulTC6pzfidbt/FhAQwHFcjQMkUUNTijd4Rf7P6ZzY2OXijPZs7JtBgwY1vjEsC9WaNWvqrAH3zwBAImJiYhQKxaxZs9iknZ1dVFRUVlbW6tWriUh8z6n6JGNmZjZ27Fh2bhETE+Ph4REQEMDG34mPj9exEsbX17e4uNjHx6exe/Vcenq6tbU1G47H5NRq9bJly5KTk1luEDaKnjhVBfuf5RJqJHZS+N133zVgXcQzAGiWtOfc0Z1eMlVRI9Ib1ejevXtNJ7dOlXRObAQ1caIolgHR0dGx8dtifUxqzOpXJ8QzAGiWWBzKzs4WSthPe2tr68ZUy76UG9yNUF9kMlmD80vo19GjR62srFhyIqZ3795ExAazZvLz84lo6NChjd9clQyF9YJ4BgDNkvacO+IrYDzPi7Oeas94Jc6nU69K9Bt+HBwcxCdAplJjOqegoCAbG5vTp08LhWlpaRYWFnp5gIGd6gl52+sF8QwAmqWwsDB3d/f4+HiWrYmI5HL5kCFD5s2bR8+via1aterWrVtxcXEsC/mJEyc0Go2rq2t+fj4LfgIhGqWmpvbv35/dltO9kmPHjtnY2LDUuHoxfPjwkpISloFIjCWCqBI7N2zY0Lt373379mmpsAErnjp1KiYmRq1Wy+VyuVyekJCwePHi48eP29raRkZGbt68mTWvpKQkMTExKiqK9XhscGOYwsJCavCpnrhzCPo3AkBToON3kZacOwqFYsCAAVZWVl5eXgqFwsPDIygoaN++feXl5eKMV7zWhE26V6JLeiMB6dC/8ezZs0T07bffigtPnz49c+ZMIjI3N1+3bt3ly5dZ+dy5c83MzDp37lxbbQ1YUXs6J57nk5KSgoKCPvzwQz8/v8TERGHFBjeG+de//iWTyYStaKGf/GcAAAZlzO8iFs+Msy1Gl3jG8/yYMWMWLVqkY503btyoM32uflc0UJ1vv/12SEiILkuivz4AQPOQkpJy/PhxXXr6KZXK+Pj4rVu31ncTDV7RQHVmZmYqFArxuCT1gngGAC80IZ+OqRtSVceOHQ8dOhQaGsqeVtaCPXXn7u5e3000eEVD1Jmfnx8dHZ2amip+BqNeEM8A4AXV9BM2ubu7R0dHy+XyOhdrWAxo8Ip6r7OysnLHjh27d+8WD6NVX03i4XMAAOOzsrKKjo6Ojo42dUO0cXFxafD4vM1IixYtxE8FNAzOzwAAQAoQzwAAQAoQzwAAQAoQzwAAQAoQzwAAQBLED1ezZ/IBAACavirjg3A8zwvzcnNz65s6CADq5O/vv2jRokGDBpm6IQCS0rVrV/HH6k/xDAAMgeO4/fv3T5o0ydQNAZAy3D8DAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApQDwDAAApaGHqBgBI0N69e0tKSsQlqampRUVFwuT48ePt7OyM3i4AKeN4njd1GwCkZtq0adu3bzc3N2eT7FPGcRwRqdXq1q1bFxQUWFpamrKJAJKD640A+hcQEEBEqucqKysrKyvZ/zKZzM/PD8EMQO9wfgagf5WVlfb29o8ePapx7qlTpzw9PY3cJADJw/kZgP61aNEiICBAuN4o1qFDh+HDhxu/SQCSh3gGYBABAQEqlapKobm5eVBQkEwmM0mTAKQN1xsBDILneScnp9zc3CrlP/744+uvv26SJgFIG87PAAyC47jAwMAqlxy7du36t7/9zVRNApA2xDMAQ6lyydHc3HzatGms1z4A6B2uNwIYkJub240bN4TJX3/9tXfv3iZsD4CE4fwMwICCgoKES45/+ctfEMwADAfxDMCAAgMDKysricjc3Pzdd981dXMApAzXGwEM629/+9vPP//McVx2draTk5OpmwMgWTg/AzCs4OBgIhowYACCGYBBYXx9Y9u4cWN6erqpWwHG8+zZM47jysvL/fz8TN0WMKoDBw6YugkvFpyfGVt6enpGRoapWwGNcvDgweoPStfmpZdesre379Kli0GbpC8ZGRl4fzZebm7uwYMHTd2K/4+9Ow2L4sr6AH6aBhRRNhUU0YgYhwTIJKMOKBodNGBcOmYGRBDaZTCKJgqKLK4J2gpRQQZwRjTBaBQRtxgkGnFBB0FN1EwSBSQMIrIIKIsgytLvh/uk3x4U6G56o/z/PvhQ1XVPnWqbPlTVrXtfOTg/0wAnJyf84dat8Xi8wMDAWbNmybh9fn7+8OHDVZqSsrCTSHw+u+jw4cOenp6azuKVg/MzAJXrLsUMoFtDPQMAAC5APQMAAC5APQMAAC5APQMAAC5APQMAAC5APQNQEycnp+DgYE1noWR3797dvn07+7mkpCQxMdHT03Ps2LFyBVG44RdffPHOO+/06dPn7bffTkxMlH7pyy+/nDVr1tq1axcuXJiUlNTFZFpaWkJDQx88eCBXeqBmeP4MQE2sra179uypuvjFxcVqfmo7IyMjISFh7969bNHS0nLy5MkLFiywtbWVK45iDcPCwoqLixcuXJiXl5eQkLBgwYL6+vqPP/6YiDZu3Pjll1/evHnTxMSkurr6nXfeqaioWLZsmcLJ8Pn8kJAQPz+/bdu2WVtby3V0oDY4PwNQk6SkpPDwcBUFLyws9Pb2VlHwl7pz545QKIyNjZWeg3vw4MGKRZO3YXFx8f379/fv379kyZIdO3acOHGCiGJiYojo/v37GzduXLRokYmJCRGZmJgsXLgwLCysqqqqK8mYmppu2LBBIBDU19fLlSqoDeoZQLf34MGD6dOnV1RUqG2PYrHYx8dn/vz5ZmZmatuptHv37kmucxKRq6tr//79Hz58SERff/11U1PTpEmTJK+6uLg0NDR88cUXXdzpW2+9ZWNjs2rVqi7GARVBPQNQudbW1pSUlHnz5k2YMIGITp48uWjRosGDB1dXV8+bN69fv34ODg4//vgjEWVnZwcFBVlbW5eXl7u7u/ft29fBweHYsWNEtHv3bh0dHR6PR0R1dXVRUVGSxb179/76669lZWX+/v5sjxcuXBg8ePClS5dUdEQnT568cePGlClTVBS/U87OzhYWFtJrnj9/Pn78eCL697//TUTSl17Z+dZPP/3U9f26ubnt3r27oKCg66FA6VDPAFROR0fHycnpq6++YicQI0eOPHjwYHFx8c6dO8PDw2NiYn755ZelS5e2trZWVVXt3LmzsLBQJBItX748Li7u3r17f/vb365cubJw4cJhw4axgH369FmxYoVkcc2aNUQ0YMCAf/7zn2xNXV3do0ePamtrVXREycnJPB5v1KhRKoovrytXrjx//nzjxo1EVFJSQkSmpqaSV9lJ5H//+9+u72jMmDHNzc2HDx/ueihQOtQzAHWQviUzaNCgQYMGEdHq1auHDBkyZ84cCwuLW7du6ejoTJs2jW0ZERExfvx4Ly8v9h0dGxtLRNJ3ql5clCYQCGpra6dPn66iw8nKyjI2NtbV1YoOZS0tLatXr/7yyy/feecdIjIyMiIidubKsJ+fP3/e9X2xk8LLly93PRQoHeoZgAZIf9sSkamp6bNnz9jPOjo6RNSrVy+2KBAIiOju3bvy7oLP53c1y/aVlZVJnwBp1meffTZp0qTZs2ezRdYvsbq6WrLB48ePicjS0rLr+2J9TMrLy7seCpQO9QxAq7FvYYX7DaoIn89vaWnRdBZERKmpqYaGhuvWrZOssbOzo9+vOjKlpaVENG7cuK7vrs0fIqBVUM8AtBrrZT558mT63+tmYrG4pqZGshmPx2tubpZuqNJ6M3DgQOkTIE05e/ZscXFxSEiIZE1WVpavr6+JicmFCxckK8+fP6+vr6+U5xnYqd6AAQO6HgqUDvUMQB2ePHlCRJIOGo2NjdKv1tXVEZF0QZJUo/T09JEjRy5atIh+v5K2adOm/Pz8mJgYdonyzJkzra2tNjY2paWl9+/fZ61OnTplYmJy+vRpFR3OhAkT6urq2EFJe/r0Kb1QSrdv325nZ3fo0KEOAirQ8Ny5cxERES0tLfHx8fHx8XFxcStWrEhLSzM1NQ0LC/vXv/7F0qurq0tISFi7di3r8ahwMkxlZSUp6VQPlE8M6uXu7u7u7q7pLKBLiCg5OVn27evr68PCwthvXFRUVEREBPt506ZNNTU1O3bsYIuhoaFPnz5lRWvbtm2VlZUPHz6MiIh48uQJi5OXl+fo6GhoaOjq6pqXlzd+/HhfX99Dhw49e/YsLCxs4MCBR48eZVuePXvW0tLy/Pnz8h6ajJ/PjIwMIvr++++lV164cOGjjz4iIj09vc8///zWrVts/ZIlS3R0dAYNGtReNAUaXrlyRXKLUYLH4/32229sgy+++MLX13fNmjUeHh4JCQmShgonw/zzn//k8/mSvbQnOTkZ367qh3dc3VDPOEDeeiYXVs9UFLxTsn8+p06dGhAQIGPY3NxcR0dHBfJRuKGKYs6YMWPhwoWdboZ6phG43ggAikhMTExLS5Olp19DQ0NsbOyePXvk3YXCDVUU8+rVq3l5edLjkoBWQT0D0C5seEDtHyTQ3Nz86NGjgYGBDQ0NHW9ZUFCwefNme3t7eXehcENVxCwtLRWJROnp6X369FFiPqBEqGcA2qK+vn7NmjWsT8eyZcuys7M1nVEn7O3tRSJRfHx8p5spVgMUbqj0mM3Nzfv27Ttw4ICaZzAAuaCegZLFxsbK9YzOl19+aW9v//bbb1tZWfF4PB6Pd/HiRZVlp9UMDQ1FIhG7E/DFF184OTlpOqPOWVtbvwrj8+rq6oaEhODMTMuhnnUzxcXFmk6hIz/88ENoaKjs2ycmJv79739ft27drVu3iouLjx8/bmxsLH2MWn68AKA9UM+6E/XPcSWX6urqEydOyDWSxb59+4jo/fffZ4szZ85MSEiQ1DAtP14A0CqoZ92G+ue4ktemTZuCg4PlutjY2tpKRNHR0ZI1f/vb31iHde0/XgDQKqhnWuqHH35wcnL6+OOP169fr6enV19fLz3HVWtra0ZGRmBgoLW1dUlJycSJE1977bXq6urGxsbPP//cz89v9OjR77333i+//MKi3b1718PDIzQ0VCgUvvvuuz///DMRNTQ0HDhwwNvb29nZOTs7+09/+tPQoUMzMzPz8vI+/PDD/v37v/HGG2xSLlnExsbOmjWLDW0ureOJuD755BMi+vTTTz/44APW85vP58+cOZP+d04vLTxeANA6mn387RUk4/OqI0aMMDMzYz97eno+fPhQLBYTka2trVgsfvbsmWR8hC1btqSnp/v5+T158mThwoU5OTmslaurq4WFRW1trVgsfv31121sbMRicVNTk4mJib29vVgsbm1tzc/PJyJjY+NTp07dvn2biIYOHbp169aampqbN28S0cSJE2U5qKysrKioKPZzm8eBv/nmm169en377bfttd2/fz8bs9zMzOxf//pXS0uL5CWtPV5S5fPUmoXn/ZUCz1NrBN5xdZPx+6J///5EFBMT09ra+ssvv7Cvacn3O/OHP/yBiB49esQWr169+uLfK6mpqWKxOCoqKikpSSwWs4H+9PT0JEGkY7JJuSQvmZubm5iYdJpqVVXVggULWltb2eKLw1s0Nzd3HKGysnLJkiVsfpPp06dLhnfSzuNlQQA6JctnCZRIK6bjgxf985//nD9//vLly/fv3x8XF/fSjsLsTpVkGqrr16/b29uza2ttBAYG1tfX79y589GjR8+ePWtqanrpTtvsxczMLCcnp9NU/f39Fy9enJeXxxbZILm5ubl6enpsAuVOJ+Lq27dvfHz8Rx99JBAIUlNTg4ODX/pIk5YcLxMQEDBmzBgZN+5G2L3MwMBATSfSvWVlZUmG5QT10XRBfeXIfj3nt99+c3NzIyI9Pb29e/eKXzhfaXMm9Nlnn/Xq1au+vl46CLt8d+3aNWtr6+++++7FVtIx27wk40CCPXv2fOlHa/jw4R03zMjIuHHjhvSagoICHo8nudCqnccrxvVG6AyuN2oE+oNoqQ0bNgwbNuz06dNJSUlNTU1r166ll81xJc3W1rahoSEyMlKy5s6dO3FxcUQkFAqbmpqmTJlCv3cpVKKnT59Kf6QkVUEypXJ7E3H16dNnxYoV0vlYW1tbWFiYm5uzRe08XgDQTrjeqKW2bdsWGBhoYmLi7u6+ePFidqdHMscVe8aLzaFVX19vaGhIRB988MGwYcPCw8OLi4snTZp0586da9euHTlyhIhKS0tra2vPnj1bUVHBpmG8du2apaVlv379iEj8+w0hdl3uyZMnvXv3lsRvbW3V0VH8755Tp07Nnj07JSWFVRdpr7/++sWLF//+97/HxsayPaamppaVlW3evJlt0B2PFwA0Bb+3WqqhoWHSpEmRkZHz5s0bP348m37Qw8PDyMjo+vXrDQ0NGzduLCwsJKIVK1bcunWLiHr06HH+/HmBQHDixImVK1c+fPjwwIED7BbR5s2bjYyM1q5da2Njs2bNGlNT082bNz958mTNmjVEVFhYeO7cue+///7evXtEtGbNmkePHsXFxbHF7du3symSFdOjRw8jI6MePXq8+FLv3r0HDhy4d+/eoUOHurq6urq6btmy5fjx4/Pnz2cbdMfjBQBN4YnRWUu9PDw8iCglJUXTiYDieDxecnLyrFmzNJ2I8uHzqRSHDx/29PTEt6ua4fwMZMJrX25urqazAwDA/TOQDf7ShFdTfn7+8OHDNZ0FyATnZwCguLt370rmay4pKUlMTPT09Bw7dqxcQVTRcP/+/QKBICwszMXFZcmSJaxbkCzi4uKkLz/ExMQQUUtLS2ho6IMHD+RKD9QM52cA2qW4uLjrk0YqJUinMjIyEhIS9u7dyxYtLS0nT568YMEC9syG7JTecNeuXYsXL05LS3v//fdv375tZ2dXWlp6/PjxTgM2NzcnJSVFRESwRV1dXaFQSER8Pj8kJMTPz2/btm3W1tZyJQlqg3oGoEUKCwuFQmF7wzerM0in7ty5IxQKb968qaenJ1kp12xB0pTbkM1DNHr0aCJ68803zc3Nz507J0u0pKQkHx8ff3//F18yNTXdsGGDQCDIzs5mT4yAtsH1RgBtoZQpctQzz45YLPbx8Zk/f76ZmZlKd6QYlhWb6Ly+vr6qqsrFxaXTVmKxODIyMiQkxNXVdcOGDez5EGlvvfWWjY3NqzAfdzeFegagErW1tSEhIWFhYStXrnRzc1u5ciW7hbN7924dHR02FmVdXV1UVJRkUXqKHCLKzs4OCgqytrYuLy93d3fv27evg4PDsWPH5ApCnU3Zo5iTJ0/euHHjxWfktUR0dLSNjU1AQEBRUVFcXNyqVasOHjzYaava2lo3NzcnJ6esrKzw8HBbW9uNGze22cbNzW337t0FBQWqSRy6Rt0DbL3yMD4eB1Bn4zfW1dWNGDHi008/ZYsPHz4cMWLEsGHDqqurxWKxjY2N9K+e9CL9PrxkS0tLamqqgYEBEX3yySeXLl06ePAge1o8MzNTxiBMp1P2SJPx8+nl5cXj8Zqaml58qc3eZafchhUVFc7OzlZWVitWrJA3YE1NjUgk0tXVJaI9e/ZIv8TmFdqyZUvHETB+o0bg/AxA+SIiIvLy8hYtWsQW+/fvv3bt2oKCAjaUl/QNpxcXGR0dnWnTprGbQxEREePHj/fy8mKnC7GxsTIGYQQbz4wxAAAgAElEQVQCQW1t7fTp07t6VFKysrKMjY3ZN752amhoMDU1dXBwiIqKCg4OFsvzwImRkdHq1avZJA87d+6UfsnCwoKILl++rNxsQSlQzwCULzMzk/53Ppp3332XiK5cuSJXHDaSJJvIlIgEAgERSQZ6ll2nU/bIq6ysTDJxjxa6du3ayJEj586de+LECWdn561bt65fv17eIH5+fgYGBpKJkBg29yybSx20DeoZgPKxOiTdoYD9XW9sbNyVsJaWltSFroBKxOfz25s2QRuEhYVVVlZOnDhRX1+fjX2akJAgbxAdHR0zM7M2D1Ozm5SgnVDPAJSPnY2dOnVKsub+/ftENHnyZPr9O/H58+dEJBaLa2pqJJt1PEUOGyhZgSBKrz0DBw6U/Qll9WNvi76+PhFZWVlZWFgoUIdKSkpKSkrYgJYSjx8/JqIBAwYoKVNQJtQzAOULDg62t7ePjY0tKytja+Lj452dnT/++GMiYg//btq0KT8/PyYmhs3ofebMmdbWVskUOdLRJNUoPT195MiR7Lac7EFOnTplYmJy+vRpJR7ghAkT6urqnjx50mb906dP6YXyuX37djs7O3ae1B7lNvT29iaitLQ0IioqKiovL589e3anMcPDw5cvX87mKG9sbPT39585c2ZoaKj0NpWVlUQ0bty4DlICTUE9A1A+AwODrKwsb2/vuXPnBgUFhYSE9O3b9/z586wDRWRkpKOjY1RU1NKlS6dNm2ZnZ+fr61tdXd3c3CyZIkc62o4dO6qqqioqKkpLSzMyMuQN0sGUPQoTCoVisTgrK0t65cWLFwMCAoiosLBw69atP/30E1tfUFCQk5MTFBTUXjSlN/T394+Pj4+Ojg4KCgoICFi/fr1k3tcOYg4ZMuTSpUujRo2aM2fO0qVL/fz8jh071mYyvMzMTD6fz8mpFbhAo70rX0Xor88B1Fl/fWWRTPatNrJ/PqdOnRoQECBj2NzcXEdHRwXyUbihimLOmDFj4cKFnW6G/voagfMzAFBEYmJiWlqaLD39GhoaYmNj9+zZI+8uFG6oophXr17Ny8uTjL8M2gb1DEB71dfXS/7VNubm5kePHg0MDGxoaOh4S/bgnb29vby7ULihKmKWlpaKRKL09HTpxzBAq6CeAWij+vr6NWvWsD4dy5Yty87O1nRGL2Fvby8Sidhzxx1vplgNULih0mM2Nzfv27fvwIEDapi1ABSmvY/3A7zKDA0NRSKRSCTSdCKdsLa2fhXG59XV1Q0JCdF0FtAJnJ8BAAAXoJ4BAAAXoJ4BAAAXoJ4BAAAXoD+IBhQXFx8+fFjTWUCXtBkagzOKi4uJCJ/PLuLqx0PL8cTyTAsEXefh4XHkyBFNZwEAKodvVzVDPQNQOR6Pl5ycjEH/AFQK988AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALUM8AAIALeGKxWNM5AHDNokWLcnNzJYs3btywtrY2NTVli3w+/6uvvrKystJQdgDcpKvpBAA4yMLCIiEhQXrNf/7zH8nPw4YNQzEDUDpcbwRQPm9v7/Ze0tfXnzdvnhpzAXhV4HojgErY29vfvn37pb9fubm5I0aMUH9KANyG8zMAlRAKhXw+v81KHo/3xz/+EcUMQBVQzwBUwsvLq6Wlpc1KPp8/d+5cjeQDwHm43gigKmPHjr169Wpra6tkDY/Hu3///qBBgzSYFQBX4fwMQFV8fX15PJ5kUUdHZ9y4cShmACqCegagKh4eHtKLPB5PKBRqKhkAzkM9A1CVfv36TZo0SdIrhMfjffjhh5pNCYDDUM8AVMjHx4fdoubz+W5ubn379tV0RgCchXoGoEJ//etf9fX1iUgsFvv4+Gg6HQAuQz0DUCFDQ8Pp06cTkb6+/owZMzSdDgCXoZ4BqNacOXOI6MMPPzQ0NNR0LgCcJlYed3d3TR8NAAB0J0qsQUoeX9/JySkwMFC5MQG6u6+//nr27Nm6uq/WdBaenp4BAQFjxozRdCLKFx0dTUT4ruuirKysHTt2KDGgMscHYU/bpKSkKCsgADc0Njb27NlT01moG4/HS05OnjVrlqYTUT581ynF4cOHPT09lViDcP8MQOVewWIGoH6oZwAAwAWoZwAAwAWoZwAAwAWoZwAAwAWoZwAA0CX5+fmaToEI9QwAtIqTk1NwcLCms1Cyu3fvbt++nf1cUlKSmJjo6ek5duxYuYKoouH+/fsFAkFYWJiLi8uSJUuqq6tljBkXF8eTEhMTQ0QtLS2hoaEPHjyQKz0lerUe8AQALWdtba3SxxuKi4utrKxUF/9FGRkZCQkJe/fuZYuWlpaTJ09esGCBra2tXHGU3nDXrl2LFy9OS0t7//33b9++bWdnV1paevz48U4DNjc3JyUlRUREsEVdXV02sR+fzw8JCfHz89u2bZu1tbVcSSoF6hkAaJGkpCTVBS8sLBQKhZcuXVLdLtq4c+eOUCi8efOmnp6eZOXgwYMVi6bchvv27SOi0aNHE9Gbb75pbm5+7tw5WaIlJSX5+Pj4+/u/+JKpqemGDRsEAkF2drb6ByzF9UYAeCU8ePBg+vTpFRUVatujWCz28fGZP3++mZmZ2nYqO5bVxYsXiai+vr6qqsrFxaXTVmKxODIyMiQkxNXVdcOGDYWFhW02eOutt2xsbFatWqX8jDuDegYAWqG1tTUlJWXevHkTJkwgopMnTy5atGjw4MHV1dXz5s3r16+fg4PDjz/+SETZ2dlBQUHW1tbl5eXu7u59+/Z1cHA4duwYEe3evVtHR4fH4xFRXV1dVFSUZHHv3r2//vprWVmZ5MTiwoULgwcPVt3p2smTJ2/cuDFlyhQVxe+i6OhoGxubgICAoqKiuLi4VatWHTx4sNNWtbW1bm5uTk5OWVlZ4eHhtra2GzdubLONm5vb7t27CwoKVJN4+5Q4trG7u7u7u7sSAwJA90VEycnJcjUpKioiIltbW7FYXFxc3Lt3byISiUT37t37+uuvicjR0bGlpSU1NdXAwICIPvnkk0uXLh08eLBPnz5ElJmZKRaLbWxspL/ZpBclwZlvvvmmV69e3377rbyHJuN3nZeXF4/Ha2pqevGlNpnITrkNKyoqnJ2draysVqxYIW/AmpoakUjERtnes2eP9Es3b94koi1btnQcITk5Wbk1COdnAKAtpG/zDBo0aNCgQUS0evXqIUOGzJkzx8LC4tatWzo6OtOmTWNbRkREjB8/3svLi50ixMbGEpH0naoXF6UJBILa2lo24aoqZGVlGRsba/O8Cg0NDaampg4ODlFRUcHBwWJ5hgY2MjJavXp1fHw8Ee3cuVP6JQsLCyK6fPmycrPtFOoZAGgpdp1QwtTU9NmzZ+xnHR0dIurVqxdbFAgERHT37l15d8Hn87uaZfvKyspMTU1VF7+Lrl27NnLkyLlz5544ccLZ2Xnr1q3r16+XN4ifn5+BgUFeXp70ShMTEyIqLy9XWq6yQT0DgG7P0tKSutD9T0X4fH5LS4ums2hXWFhYZWXlxIkT9fX1Dx06REQJCQnyBtHR0TEzMxs+fLj0yjZ/iKgN6hkAdHtVVVVENHnyZPr9y/T58+dExG7zSDbj8XjNzc3SDVVabwYOHCj7E8rqx94ifX19IrKysrKwsFCgDpWUlJSUlLAJ4SQeP35MRAMGDFBSprJCPQMAbfHkyRMiqq2tZYuNjY3Sr9bV1RGRdEGSVKP09PSRI0cuWrSIiNhTw5s2bcrPz4+JiWGXKM+cOdPa2mpjY1NaWnr//n3W6tSpUyYmJqdPn1bR4UyYMKGuro4dlLSnT5/SC6V0+/btdnZ27DypPcpt6O3tTURpaWlEVFRUVF5ePnv27E5jhoeHL1++PCcnh4gaGxv9/f1nzpwZGhoqvU1lZSURjRs3roOUVAH1DAC0QkNDw+bNm4mopKQkOjo6MjKSPdskEolqa2tjYmLYQErr1q2T1LkdO3ZUVVVVVFSUlpZmZGSwnheRkZGOjo5RUVFLly6dNm2anZ2dr69vdXV1c3Ozh4eHkZHR9evXWfMePXoYGRn16NFDRUckFArFYnFWVpb0yosXLwYEBBBRYWHh1q1bf/rpJ7a+oKAgJycnKCiovWhKb+jv7x8fHx8dHR0UFBQQELB+/frIyMhOYw4ZMuTSpUujRo2aM2fO0qVL/fz8jh07xm5nSmRmZvL5fA1MTa7EvpLorw8AEiR/f33ZsZMwFQXvlOzfdVOnTg0ICJAxbG5urqOjowL5KNxQRTFnzJixcOHCTjdDf30AgG4jMTExLS1Nlp5+DQ0NsbGxe/bskXcXCjdUUcyrV6/m5eVJxl9WJ83UM8n18W4UWT0ePnyYkpLCrrqAcnW7zwY+DB2or6+X/KvNzM3Njx49GhgY2NDQ0PGWBQUFmzdvtre3l3cXCjdURczS0lKRSJSens6ecFcztdazlpaWyMjI8ePH9+3bV+nBt23bNmHCBFVEVpucnJzw8PBZs2bt379fslK502eoejKOL7744p133unTp8/bb7+dmJgoS5Ply5f369ePx+Pp6enNmDFjypQpo0ePnjJlypEjR5SVVQefjcOHD7/99ts8Hs/e3p7dM2fOnTs3ZcoUHo83evTow4cPKysT2XHgw6Ai9fX1a9asYX06li1blp2dremMOmFvby8Sidhzxx1vplgNULih0mM2Nzfv27fvwIEDap7B4P8p8dqlLNeUnz59ygbBlDf4/fv3O96gsbGRfWHJG1mrsBvd0sPSzJ49e926dQoHbPO+dTFax0JDQ318fOLj45cvX86GI4qNjZWlYWlpKRGNGDGCLT579ozdvt62bZsszbv42ZD05/7oo4+k17POCLm5ubLkoArd+sMgVvH9M81CXwGlUPr9Mw30B1HgRu5///vf8ePHqyKyFiJFx2d7kYzvm1Lcv39/zpw5ksUzZ84Q0fDhw2Vs3uaom5qaDAwMhg0b1mlDpXw2iOjdd99t8/3b1NRERM+fP+80uOp00w8Dg3oGHXsV+4Oof5YHblDz+3bv3j3pO8Curq79+/d/+PChYtF0dXX79OnT6R0vJR5jcnLywIEDFy5c+N///leSA3U4+l83gl8ieBVorJ7l5+cLBAIzM7M///nPbAIeIrp7966Hh0doaKhQKHz33Xd//vlnetksD/X19Zs2bfL19V2+fPnEiRPZVN8SFRUVbAoJe3v7H374oeM0OpiTgohqa2tDQkLCwsJWrlzp5ua2cuXK6urq1tbWjIyMwMBAa2vrkpKSiRMnvvbaayUlJQcOHPD29nZ2ds7Ozv7Tn/40dOjQzMzMvLy8Dz/8sH///m+88YYkbHtH2kab6TOIyMzMbPbs2YGBgYGBgQMGDODz+exJGlnetxejvfToOn1P2uPs7MwGIZV4/vz5+PHj2c/yTsxx5MiRhw8fLliwoON3TImfjQEDBhw+fLihocHT05OdmbWBD4PsHwYAzVDiuZ5c1xsDAgLOnj27a9cuQ0NDPp//n//8RywWv/766zY2NmKxuKmpycTExN7enjUhqasuTU1NEydO9PX1bW1tFYvFrNMBm/GBRWZTzJ06dYqIxowZ03Ey7c1JIRaL6+rqRowY8emnn7ItHz58OGLEiGHDhj18+PDKlStsINQtW7akp6f7+fnV1dXl5+cTkbGx8alTp27fvk1EQ4cO3bp1a01NDZs9YeLEiZL9tnekbQ5WevqM5uZmSTJsRIOQkJCOo9H/Xq2Sjtbe0VVXV3fwnsguMzPTwMDgxo0bbLHTiTnYWzdv3jwfH5+xY8eampomJCSw/2LZj1Hhz4bkFyE6OpqIgoKC2qzHh0GBDwPheiN0SOnXG3lieSYI6BgbwislJaXjzd54442cnJza2lrWf+Yf//jH8uXL586du3fv3ujo6IEDB86ePVssFr/++utFRUVshDEej2dra3vnzh0iio6OXrFiRW5u7ogRI4iopaVl//79M2fONDExYZFbW1vZKGT9+vV7+vRppz16bW1t2T1/tjhgwIDq6urGxsa1a9eKRKLS0lLJKGT79+8XCoXBwcGRkZGs1aNHj6THz5bO08rK6sGDB5KwFhYWz58/Z8OasaN46ZG2CdJmsbGxsWfPntXV1fb29mZmZj/88AMbe02W961NNFmO7sX3pON3UqKlpWXSpEmLFy+WDJ/DVnYwljmPxxs+fPi5c+caGhru379//PjxxMTEpUuXfv7552zoAZV+Nni8//9F8PT0TElJSU1NnTp1qmQ9PgwKfBh4PF5AQMCYMWM63bLbYX/3BAYGajqR7i0rK2vHjh1KrEGa7w9y7949Iho9ejRbfPLkSXx8/MaNG1mPT7aSpP60ZBND1NfXdxpZxu4h7bWaOHEiET158kTyEuvwNm7cuPaCS+fZaTIvPVLxC39H0ws9Anx9ffX19W/dutVptBfbStbIdXTydrRZt25deHi47Nu/NFU2l1VERIRkjeo+G9I/19XVvfHGG/3792ejK7GV+DB0kHx7lPUdBdwmy2dJRprvD8JuugwZMoSIrl+/7uDgMGzYsLVr17KrHC9iT9orMNGRvNhpAfvFlk7V2Ni468FlOdKXOnHixP79+z/77LM//vGPXYmmuqNLTU01NDRct25dF+Ow0/1vvvmGLarts9G7d+9jx449ffrUx8dHshIfBsXgeiN0gF1vVCLN1zP2XCSbIlYoFDY1NU2ZMoWIWltbJdtIz/LAfnVFIpH49z8A792799133yk9MdaBm91rkU6VzUnRRe0daccqKysXLVo0ZsyYVatWsTVsaFFZ3rc2VHR0Z8+eLS4uDgkJkayRDMYq78QcrDgNHDiQLarus8GiSce0tbX98ssvL1y4IFmDDwNAN6DEYivj3yxvvPEGET169IgtLlmy5IMPPmA/Gxsb83i877///sCBA+bm5kR09erV+/fvDx8+3NDQsKioSCwWFxQUGBoaEpGLi0t8fPy6desWLVrE7v+zOf1qa2tZNPZVKH0V5aWGDh0q/T6wKd6bmpoaGhrs7e2trKxKS0vZS8uXL3d2dm5qapK0kg7ORpf4wx/+wBZtbGyIqK6uTnovLS0tHR8pGxRn6NChbDM2QYalpSVb/Nvf/mZoaHj37l22+OjRo9DQUBnftzbRZDm6F9+Tjt/J9PR0FxeXuN/FxsYGBgauXbtWLBanpqb27t37u+++e2lD9tYNGTJEsqa8vHzs2LH6+vrXrl3r+B3r+meDPc1dUlLSJit2d4T9jA+D5NBk/DCI0R8EOsOF56nPnj07Y8aMiRMnfvTRR8uWLYuPj5f8YsfHxxsbG//5z3/Ozs6OiYkxNTX94IMPqqqqwsLCBg4cePToUbbZzz//7ObmZmpqOmjQoICAgJqamtbW1q1bt7IKHRAQ8OTJk88//5wtrly58tmzZ+0lIxmEZtOmTTU1NTt27GCLoaGhT58+raurCw4OdnV1XblyZXBwcHh4+LNnz+rr68PDw9lmH3300c2bN8VicXl5+YoVK4ioR48e6enpZ86cYU8vLVu2rKqqKjY2lnVD+PzzzysrK9s70h9++GHZsmUs8o4dOx48eBAWFsYWo6KiWG89e3v7gICAgICAv//978OHD4+KipLxfauvr5eOVltb+9Kj6/Q9ae+dlHTzk8bj8X777Tf2n25paXn+/PkXGx49etTd3Z1t7+joOGXKlLFjx77xxhteXl6//PKL9P+UKj4bhw4dmjp1KhFNnz798uXL0ok1NTWxG0gMPgyyfxgY1DPoGBf6NwLAq4DH4yUnJ2tgEizVw3edUhw+fNjT01OJNUjz98/UgNe+3NxcTWfXneCdBACtpavpBNRBifX/FYd3EgC01itxfgYAAKrDBsTRONQzAADVunv3rmS07pKSksTERE9Pz7Fjx8oVRBUN9+/fLxAIwsLCXFxclixZwgbtlEVcXJz07QY2UGpLS0toaCgbiEAjXonrjQDAMcXFxV2fNFIpQTqVkZGRkJCwd+9etmhpaTl58uQFCxawkVZkp/SGu3btWrx4cVpa2vvvv3/79m07O7vS0tLjx493GrC5uTkpKSkiIoIt6urqCoVCIuLz+SEhIX5+ftu2bbO2tpYrSaVAPQOAbqawsFAoFMo+XYPqgnTqzp07QqHw5s2b0hMPDR48WLFoym24b98+Iho9ejQRvfnmm+bm5ufOnZMlWlJSko+Pj2RSC2mmpqYbNmwQCATZ2dnsYVB1wvVGAOhOlDKXm3omhBOLxT4+PvPnzzczM1PpjhTDsmLTddXX11dVVbm4uHTaSiwWR0ZGhoSEuLq6sgkr2mzw1ltv2djYSIatUSfUMwDQmPbmXdu9e7eOjg578Lyuri4qKkqy2GYut+zs7KCgIGtr6/Lycja5nYODw7Fjx+QKQvJP0SeLkydP3rhxg409poWio6NtbGwCAgKKiori4uJWrVp18ODBTlvV1ta6ubk5OTllZWWFh4fb2tpu3LixzTZubm67d+8uKChQTeLtU+Kz2XhmHgAkqLPxQTqYd038+yBhko2lF+n3mQFaWlpSU1MNDAyI6JNPPrl06dLBgwfZRFSZmZkyBmE6naJPmozfdV5eXjwe76Vjg9EL0x3ISLkNKyoqnJ2draysVqxYIW/AmpoakUjExr7Zs2eP9Etskr8tW7Z0HEHp44Pg/AwANCMiIiIvL2/RokVssX///mvXri0oKNi8eTMRSd9wenGR0dHRmTZtGrs5FBERMX78eC8vL3a6wOYbkiUIIxAIamtr2cDoypKVlWVsbMy+8bVTQ0ODqampg4NDVFRUcHCwWJ4HTI2MjFavXs1GRNu5c6f0S2x+hsuXLys3206hngGAZmRmZhIRO51i2Ej/V65ckSsOm+9GMnwomwZPgWmDOphvVjFlZWXSU7xqm2vXro0cOXLu3LknTpxwdnbeunXr+vXr5Q3i5+dnYGCQl5cnvdLExIR+nyJDnVDPAEAzVDTvGptLQeGugErE5/PlnSZJncLCwiorKydOnKivr3/o0CEiSkhIkDeIjo6OmZnZ8OHDpVeym5Tqh3oGAJrR8bxr7Dvx+fPnRMTu1kg262AuNyKqqqpSLIjSa8/AgQNlf0JZ/djboq+vT0RWVlYWFhYK1KGSkpKSkhI2QLPE48ePiWjAgAFKylRWqGcAoBnBwcH29vaxsbFlZWVsTXx8vLOz88cff0xE7OHfTZs25efnx8TEPHv2jIjOnDnT2tpqY2NTWlrKip+EpBqlp6ePHDmS3ZaTPcipU6dMTExOnz6txAOcMGFCXV3dkydP2qxn0+O1KZ/bt2+3s7Nj50ntUW5Db29vIkpLSyOioqKi8vLy2bNndxozPDx8+fLlOTk5RNTY2Ojv7z9z5szQ0FDpbSorK4lo3LhxHaSkCqhnAKAZBgYGWVlZ3t7ec+fODQoKCgkJ6du37/nz51kHisjISEdHx6ioqKVLl06bNs3Ozs7X17e6urq5udnDw8PIyOj69evS0Xbs2FFVVVVRUVFaWpqRkSFvkB49ehgZGfXo0UOJBygUCsVisWSKdubixYsBAQFEVFhYuHXrVjarOBEVFBTk5OQEBQW1F03pDf39/ePj46Ojo4OCggICAtavXx8ZGdlpzCFDhly6dGnUqFFz5sxZunSpn5/fsWPH2KVjiczMTD6fr4GpgpTYVxL99QFAgtQ1nyc7CVPDjiRk/66bOnVqQECAjGFzc3MdHR0VyEfhhiqKOWPGjIULF3a6GfrrAwB0G4mJiWlpabL09GtoaIiNjd2zZ4+8u1C4oYpiXr16NS8vTzL+sjqhngFA91ZfXy/5V9uYm5sfPXo0MDCwoaGh4y3Zg3f29vby7kLhhqqIWVpaKhKJ0tPTpR/DUBvUMwDorurr69esWcP6dCxbtiw7O1vTGb2Evb29SCRizx13vJliNUDhhkqP2dzcvG/fvgMHDqhh1oKX0t4H1wEAOmZoaCgSiUQikaYT6YS1tbVGxudVM11d3ZCQEA0mgPMzAADgAtQzAADgAtQzAADgAtQzAADgAiX3B8nOzm4zkBcAvLKio6NTUlI0nYXysY6U+K7rouLiYuUG5InlmfCmY1FRUW1GdgEAIvruu+/eeecd9Q/PCqD9lPgXjzLrGQC8FI/HS05O1sBwdgCvEtw/AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALkA9AwAALtDVdAIAHFRdXS0Wi6XX1NfXP378WLLYu3dvPT09tecFwGW8Nr91ANB1Li4uFy5caO9VPp//4MEDCwsLdaYEwHm43gigfF5eXjwe76Uv6ejovPvuuyhmAEqHegagfO7u7rq6L7+Yz+PxhEKhmvMBeBWgngEon6mpqaurK5/Pf/ElHR2dDz/8UP0pAXAe6hmASvj4+LS2trZZqaurO23aNGNjY42kBMBtqGcAKiEQCHr06NFmZUtLi4+Pj0byAeA81DMAlejVq9eHH37YplO+gYHB1KlTNZUSALehngGoire3d1NTk2RRT0/P3d3dwMBAgykBcBjqGYCquLm5Sd8qa2pq8vb21mA+ANyGegagKnp6eqD9froAACAASURBVLNnz9bX12eLJiYmkyZN0mxKAByGegagQl5eXs+fPyciPT09Hx+f9h5KA4Cuw3hXACrU2tpqaWlZXl5ORP/+97+dnZ01nREAZ+H8DECFdHR0fH19iWjgwIFjx47VdDoAXIarH9olKyvr/v37ms4ClKlfv35E5OjomJKSoulcQMlmzZql6RTg/+F6o3bx8PA4cuSIprMAAJng+1Or4Hqj1nF3dxeDphFRcnKysqKlpKQoK1TXubu74zPWdcnJyZr+qoC2UM8AVM7d3V3TKQBwH+oZAABwAeoZAABwAeoZAABwAeoZAABwAeoZAABwAeoZALzS8vPzNZ0CKAfqGYDSODk5BQcHazoLJbt79+727dvZzyUlJYmJiZ6envKO3aWKhvv37xcIBGFhYS4uLkuWLKmurpYxZlxcHE9KTEwMEbW0tISGhj548ECu9ECrYLwrAKWxtrbu2bOn6uIXFxdbWVmpLv6LMjIyEhIS9u7dyxYtLS0nT568YMECW1tbueIoveGuXbsWL16clpb2/vvv3759287OrrS09Pjx450GbG5uTkpKioiIYIu6urpCoZCI+Hx+SEiIn5/ftm3brK2t5UoStATqGYDSJCUlqS54YWGhUCi8dOmS6nbRxp07d4RC4c2bN/X09CQrBw8erFg05Tbct28fEY0ePZqI3nzzTXNz83PnzskSLSkpycfHx9/f/8WXTE1NN2zYIBAIsrOzDQ0NFcsWNAjXGwG6gQcPHkyfPr2iokJtexSLxT4+PvPnzzczM1PbTmXHsrp48SIR1dfXV1VVubi4dNpKLBZHRkaGhIS4urpu2LChsLCwzQZvvfWWjY3NqlWrlJ8xqB7qGYAStLa2pqSkzJs3b8KECUR08uTJRYsWDR48uLq6et68ef369XNwcPjxxx+JKDs7OygoyNraury83N3dvW/fvg4ODseOHSOi3bt36+jo8Hg8Iqqrq4uKipIs7t2799dffy0rK5OcWFy4cGHw4MGqO107efLkjRs3pkyZoqL4XRQdHW1jYxMQEFBUVBQXF7dq1aqDBw922qq2ttbNzc3JySkrKys8PNzW1nbjxo1ttnFzc9u9e3dBQYFqEgdV0vSonvA/MFasliD5xyMuKioiIltbW7FYXFxc3Lt3byISiUT37t37+uuvicjR0bGlpSU1NdXAwICIPvnkk0uXLh08eLBPnz5ElJmZKRaLbWxspH8rpRclwZlvvvmmV69e3377rbyHJuNnzMvLi8fjNTU1vfhSm0xkp9yGFRUVzs7OVlZWK1askDdgTU2NSCRi04Xv2bNH+qWbN28S0ZYtWzqOwMYjlne/oFI4PwNQDunbPIMGDRo0aBARrV69esiQIXPmzLGwsLh165aOjs60adPYlhEREePHj/fy8mKnCLGxsUQkfafqxUVpAoGgtrZ2+vTpKjqcrKwsY2Nj9o2vnRoaGkxNTR0cHKKiooKDg8XyTN1iZGS0evXq+Ph4Itq5c6f0SxYWFkR0+fJl5WYLaoB6BqAS7DqhhKmp6bNnz9jPOjo6RNSrVy+2KBAIiOju3bvy7oLP53c1y/aVlZWZmpqqLn4XXbt2beTIkXPnzj1x4oSzs/PWrVvXr18vbxA/Pz8DA4O8vDzplSYmJkRUXl6utFxBXVDPADTM0tKSutD9T0X4fH5LS4ums2hXWFhYZWXlxIkT9fX1Dx06REQJCQnyBtHR0TEzMxs+fLj0yjZ/iEA3gnoGoGFVVVVENHnyZPr9y/T58+dEJBaLa2pqJJvxeLzm5mbphiqtNwMHDpT9CWX1Y2+Rvr4+EVlZWVlYWChQh0pKSkpKSjw8PKRXPn78mIgGDBigpExBfVDPAJTjyZMnRFRbW8sWGxsbpV+tq6sjIumCJKlG6enpI0eOXLRoERGxp4Y3bdqUn58fExPDLlGeOXOmtbXVxsamtLT0/v37rNWpU6dMTExOnz6tosOZMGFCXV0dOyhpT58+pRdK6fbt2+3s7Nh5UnuU29Db25uI0tLSiKioqKi8vHz27NmdxgwPD1++fHlOTg4RNTY2+vv7z5w5MzQ0VHqbyspKIho3blwHKYF2Qj0DUIKGhobNmzcTUUlJSXR0dGRkJHu2SSQS1dbWxsTEsIGU1q1bJ6lzO3bsqKqqqqioKC0tzcjIYD0vIiMjHR0do6Kili5dOm3aNDs7O19f3+rq6ubmZg8PDyMjo+vXr7PmPXr0MDIy6tGjh4qOSCgUisXirKws6ZUXL14MCAggosLCwq1bt/70009sfUFBQU5OTlBQUHvRlN7Q398/Pj4+Ojo6KCgoICBg/fr1kZGRncYcMmTIpUuXRo0aNWfOnKVLl/r5+R07dozdzpTIzMzk8/mzZs3q5A0CLaTh/pXwv9BfX0uQ/P31ZcdOwlQUvFOyf8amTp0aEBAgY9jc3FxHR0cF8lG4oYpizpgxY+HChZ1uhv76WgjnZwDwcomJiWlpabL09GtoaIiNjd2zZ4+8u1C4oYpiXr16NS8vTzL+MnQvqGevrocPH6akpLCrZKBO9fX1kn+1mbm5+dGjRwMDAxsaGjresqCgYPPmzfb29vLuQuGGqohZWloqEonS09PZE+7Q7aCevaJycnLCw8NnzZq1f//+Lob64osv3nnnnT59+rz99tuJiYmyNMnIyHB1dWWzdbi4uEyePHncuHHe3t63b9/utO3FixdnzZrF2i5evPjKlSttNjh79uycOXPYBnPnzr1z5w5bf/ny5ZkzZ/J4vAkTJnzzzTfyHqZS1NfXr1mzhvXpWLZsWXZ2tkbSkJ29vb1IJGLPHXe8mWI1QOGGSo/Z3Ny8b9++AwcOqHkGA1AmTV/whP+hzvtnrGOCYuMPSYSGhvr4+MTHxy9fvpwN4xQbGytLw+LiYiIaNmwYW3zy5Mns2bN1dXVPnTrVaVt2uvDaa6+1twE7NBMTk9bWVun1paWlRFRSUtLpLkiV9880C/dolQL3z7QQzs9eXV3vGldcXHz//v39+/cvWbJkx44dJ06cICI2O2Kn2HBQ7PkhIjI0NNyyZUtzc/M//vGPTtuywsn+fSl2aAMGDGjzTJK5uTn9PqARAHAM6hko7t69e9J3zl1dXfv37//w4UPForFrRNJPECsd65ndpn82AHADfrG7mdbW1oyMjMDAQGtr65KSkokTJ7722mvV1dWNjY2ff/65n5/f6NGj33vvvV9++UWusB3MVNIBZ2fnNuc6z58/Hz9+PPtZ3glN2AWc9957T7KmiwcFAK8U1LNuprm5WV9fPyEhobCwcN++fevWrXN1ddXT01u2bNkHH3ywZ8+e69ev6+joTJ48mQ1IIaOFCxcOGzaM/dynT58VK1ZIFmV35cqV58+fSyaUqqure/TokWS8jJdqbGy8evXqt99+u3DhwsDAwHnz5q1Zs0byahcPCgBeKTyxPJMsgKqxoeRSUlI63szW1jY3N/fRo0dsBPRr1645Ojq22SY1NXXatGkdx+HxeLa2tqwH4BtvvJGTkyP5PLRZ7FRLS8ukSZMWL14sGXaIrexgDHgej9e3b9+PP/74888/19fXv3Xr1tChQyWvdnxQ0pl3emht1styUDwez8nJiZNd3VinSicnJ00n0r0VFxdnZ2fj+1Or4PysW2JXAiXTeVy/ft3e3r5NV59Oi5lyffbZZ5MmTZIuZiTDhCb9+/f/9NNP4+Pja2pq2KyMkpe6eFB6enqtra1tVra0tHQwoxgAdGvaO1kfyK6qqqqgoKChoUEypRYRtba2qq3jQ2pqqqGhYUhIiGLN58+fn5GR8dVXX4lEorVr17KVih1URUWFqamprq7u0KFDX+xa8ujRo379+smYVWBgICcH8ZPxGgB07PDhw56enprOAv4Hzs+4wNbWtqGhQTIeKxHduXMnLi5OriAdzFTSsbNnzxYXF0sXM8kgtrJPaLJz5047O7sNGzacOnWKrVHsoJYsWcJOCkeOHFleXs4GBZa4ePGipLsKAHAMzs+6Jfa8cH19vaGhIRF98MEHw4YNCw8PLy4unjRp0p07d65du3bkyJGOg7BpOCTDvbO7TZs2bRIKhampqZKZSt57770OTonOnTsXERHx17/+lQ0hIRaLCwoKDA0Nx4wZc+rUqdmzZ6ekpEyZMuXFhux56vLycrFYzOPxevXqlZKSMnr06Dlz5ly7dm3EiBEdHBR7LLquro61ZQFra2tXrVrVs2dPtiY8PPzEiRMeHh7Hjx+3srJqamr6/vvvly1b9t1338n5ZgNAN6Hax7VBTp2O3VBfXx8eHs7+7z766KObN2+y9YWFhQKBwMzMbMCAAR999FFFRUXHOyooKFi2bBmLs2PHjsePH+fl5Tk6OhoaGrq6uubl5Y0fP97X1/fQoUPPnj1rL8iVK1ekLwYyPB7vt99+E4vFZ8+etbS0PH/+/IsNr169umDBArb94sWL//Of/7D1+/btI6KBAwfu2rWrvYM6f/78Bx98wNra2tr+5S9/+ctf/vKHP/yBPUP91VdfSfaSm5vr7u4+bNgwa2vroUOHzpo16+eff+74bZEgjA8CHcL4IFoI/Ru1C+5taAkej5ecnIz7Z9Aedv8M359aBffPuIzXvtzcXHUGAQBQNdw/4zKl/PGIv0CB2/Lz84cPH67pLEAJcH4GAB25e/euZJTOkpKSxMRET0/PsWPHyhVEFQ33798vEAjCwsJcXFyWLFlSXV0tY8y4uDjpywxsBO2WlpbQ0NAHDx7IlR5oFZyfAahbcXFx10ceUUqQTmVkZCQkJOzdu5ctWlpaTp48ecGCBba2tnLFUXrDXbt2LV68OC0t7f333799+7adnV1paenx48c7Ddjc3JyUlBQREcEWdXV1hUIhEfH5/JCQED8/v23btllbW8uVJGgJ1DMAtSosLBQKhbIP06y6IJ26c+eOUCi8efOm9KAqgwcPViyachuyrrCjR48mojfffNPc3PzcuXOyREtKSvLx8fH393/xJVNT0w0bNggEguzsbPYkDHQvuN4IoD4PHjyYPn16RUWFxoN0SiwW+/j4zJ8/38zMTKU7UgzL6uLFi0RUX19fVVXl4uLSaSuxWBwZGRkSEuLq6rphw4Y2j9sT0VtvvWVjY7Nq1SrlZwyqh3oGoKDa2tqQkJCwsLCVK1e6ubmtXLmS3cLpYPKdvXv3/vrrr2VlZez8IDs7OygoyNraury83N3dvW/fvg4ODseOHZMrCMk/NY8sTp48eePGjZc+C68NoqOjbWxsAgICioqK4uLiVq1adfDgwU5b1dbWurm5OTk5ZWVlhYeH29raSqaDkHBzc9u9e3dBQYFqEgdV0uTDb/ACPOuqJaiz56nr6upGjBjx6aefssWHDx+OGDFi2LBh1dXVYrHYxsZG+pdLepGIbG1txWJxS0tLamoqm2X7k08+uXTp0sGDB9mkppmZmTIGYb755ptevXp9++23shyajJ8xLy8vHo/X1NT04ktt9i475TasqKhwdna2srJiI1nLpaamRiQS6erqEtGePXukX7p58yYRbdmypeMIeJ5aC+H8DEAREREReXl5ixYtYov9+/dfu3ZtQUHB5s2biajNKP4vHdRfR0dn2rRp7OZQRETE+PHjvby82OlCbGysjEEYgUBQW1s7ffr0rh6VlKysLGNjY/aNr50aGhpMTU0dHByioqKCg4PF8jxYYmRktHr1ajZI286dO6VfYlPUXr58WbnZghqgngEoIjMzk4jY6RTz7rvvEtGVK1fkisPGxpQMGyYQCIjo7t278ubT6dQ88iorK5NMSKSFrl27NnLkyLlz5544ccLZ2Xnr1q3r16+XN4ifn5+BgUFeXp70ShMTEyIqLy9XWq6gLqhnAIpgdUi6QwH7u97Y2LgrYS0tLakLXQGViM/nyz49gvqFhYVVVlZOnDhRX1//0KFDRJSQkCBvEB0dHTMzszYPU0tGuIZuB/UMQBHsbEwyuw0R3b9/n4gmT55MHU6+w+Pxmpub2wtbVVWlWBCl156BAwfK/oSy+rG3RV9fn4isrKwsLCwUqEMlJSUlJSVsQEuJx48fE9GAAQOUlCmoD+oZgCKCg4Pt7e1jY2PLysrYmvj4eGdn548//piI2MO/mzZtys/Pj4mJkUy+09raamNjU1payoqfhKQapaenjxw5kt2Wkz3IqVOnTExMTp8+rcQDnDBhQl1d3ZMnT9qsZ9MMtSmf27dvt7OzY+dJ7VFuQ29vbyJKS0sjoqKiovLycsnc6B3EDA8PX758eU5ODhE1Njb6+/vPnDkzNDRUepvKykoiGjduXAcpgXZCPQNQhIGBQVZWlre399y5c4OCgkJCQvr27Xv+/HnWgSIyMtLR0TEqKmrp0qXTpk2zs7Pz9fWtrq5ubm728PAwMjK6fv26dLQdO3ZUVVVVVFSUlpZmZGTIG6RHjx5GRkZsxhxlEQqFYrFYMjUrc/HixYCAACIqLCzcunXrTz/9xNYXFBTk5OQEBQW1F03pDf39/ePj46Ojo4OCggICAtavXy+Z+rWDmEOGDLl06dKoUaPmzJmzdOlSPz+/Y8eOtZneLzMzk8/nc3JqBe7TaO9KaAv99bUEqWv+M3YSpoYdScj+GZs6dWpAQICMYXNzcx0dHRXIR+GGKoo5Y8aMhQsXdroZ+utrIZyfAcDLJSYmpqWlydLTr6GhITY2ds+ePfLuQuGGKop59erVvLw8yfjL0L2gngFoUn19veRfbWNubn706NHAwMCGhoaOt2QP3tnb28u7C4UbqiJmaWmpSCRKT0+XfgwDuhHUMwDNqK+vX7NmDevTsWzZsuzsbE1n9BL29vYikYg9d9zxZorVAIUbKj1mc3Pzvn37Dhw4oIZZC0BFtPfhfwBuMzQ0FIlEIpFI04l0wtra+lUYn1dXVzckJETTWUCX4PwMAAC4APUMAAC4APUMAAC4APUMAAC4APUMAAC4gCeWZ9IgUDUPD48jR45oOgsAkAm+P7UK6pl2ycrKajNSLXCAp6dnQEDAmDFjNJ0IKBmGedQqqGcAKsfj8ZKTk/HdB6BSuH8GAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcgHoGAABcoKvpBAA4KCkpqa6uTnpNenp6dXW1ZPHDDz/s37+/2vMC4DKeWCzWdA4AXDNv3ryvvvpKT0+PLbLfMh6PR0QtLS29e/d++PBhjx49NJkiAOfgeiOA8nl5eRFR0++am5ubm5vZz3w+38PDA8UMQOlwfgagfM3NzRYWFo8ePXrpq+fOnXNxcVFzSgCch/MzAOXT1dX18vKSXG+U1q9fvwkTJqg/JQDOQz0DUAkvL6+mpqY2K/X09Hx9ffl8vkZSAuA2XG8EUAmxWDxkyJDi4uI2669duzZ69GiNpATAbTg/A1AJHo/n4+PT5pLj4MGDR40apamUALgN9QxAVdpcctTT05s3bx7rtQ8ASofrjQAqZGtrm5ubK1n85Zdf7OzsNJgPAIfh/AxAhXx9fSWXHN98800UMwDVQT0DUCEfH5/m5mYi0tPTmzt3rqbTAeAyXG8EUK1Ro0b9+OOPPB6vsLBwyJAhmk4HgLNwfgagWkKhkIgcHR1RzABUCuPrq1tUVFRWVpamswD1aWxs5PF4z5498/Dw0HQuoFYpKSmaTuHVgvMzdcvKysrOztZ0FtAlR44cefFB6fb07NnTwsLCyspKpSkpS3Z2Nj6fXVdcXHzkyBFNZ/HKwfmZBjg5OeEPt26Nx+MFBgbOmjVLxu3z8/OHDx+u0pSUhZ1E4vPZRYcPH/b09NR0Fq8cnJ8BqFx3KWYA3RrqGQAAcAHqGQAAcAHqGQAAcAHqGQAAcAHqGQBAu/Lz8zWdAsgK9QxATZycnIKDgzWdhZLdvXt3+/bt7OeSkpLExERPT8+xY8fKFUQVDffv3y8QCMLCwlxcXJYsWVJdXS1jzLi4OJ6UmJgYImppaQkNDX3w4IFc6YGa4fkzADWxtrbu2bOn6uIXFxer+antjIyMhISEvXv3skVLS8vJkycvWLDA1tZWrjhKb7hr167FixenpaW9//77t2/ftrOzKy0tPX78eKcBm5ubk5KSIiIi2KKuri4brozP54eEhPj5+W3bts3a2lquJEFtUM8A1CQpKUl1wQsLC4VC4aVLl1S3izbu3LkjFApv3rwpPQf34MGDFYum3Ib79u0jotGjRxPRm2++aW5ufu7cOVmiJSUl+fj4+Pv7v/iSqanphg0bBAJBdna2oaGhYtmCSuF6I0C39+DBg+nTp1dUVKhtj2Kx2MfHZ/78+WZmZmrbqexYVhcvXiSi+vr6qqoqFxeXTluJxeLIyMiQkBBXV9cNGzYUFha22eCtt96ysbFZtWqV8jMGZUA9A1C51tbWlJSUefPmTZgwgYhOnjy5aNGiwYMHV1dXz5s3r1+/fg4ODj/++CMRZWdnBwUFWVtbl5eXu7u79+3b18HB4dixY0S0e/duHR0dHo9HRHV1dVFRUZLFvXv3/vrrr2VlZZITiwsXLgwePFh1p2snT568cePGlClTVBS/i6Kjo21sbAICAoqKiuLi4latWnXw4MFOW9XW1rq5uTk5OWVlZYWHh9va2m7cuLHNNm5ubrt37y4oKFBN4tA1YlAvd3d3d3d3TWcBXUJEycnJcjUpKioiIltbW7FYXFxc3Lt3byISiUT37t37+uuvicjR0bGlpSU1NdXAwICIPvnkk0uXLh08eLBPnz5ElJmZKRaLbWxspH9npRclwZlvvvmmV69e3377rbyHJuPn08vLi8fjNTU1vfhSm0xkp9yGFRUVzs7OVlZWK1askDdgTU2NSCTS1dUloj179ki/dPPmTSLasmVLxxGSk5Px7ap+OD8DUAfp2zyDBg0aNGgQEa1evXrIkCFz5syxsLC4deuWjo7OtGnT2JYRERHjx4/38vJipwixsbFEJH2n6sVFaQKBoLa2dvr06So6nKysLGNjY/aNr50aGhpMTU0dHByioqKCg4PF8kxcbGRktHr16vj4eCLauXOn9EsWFhZEdPnyZeVmC0qBegagAew6oYSpqemzZ8/Yzzo6OkTUq1cvtigQCIjo7t278u6Cz+d3Ncv2lZWVmZqaqi5+F127dm3kyJFz5849ceKEs7Pz1q1b169fL28QPz8/AwODvLw86ZUmJiZEVF5errRcQXlQzwC0mqWlJXWh+5+K8Pn8lpYWTWfRrrCwsMrKyokTJ+rr6x86dIiIEhIS5A2io6NjZmbWZm6ENn+IgFZBPQPQalVVVUQ0efJk+v3L9Pnz50QkFotramokm/F4vObmZumGKq03AwcOlP0JZfVjb5G+vj4RWVlZWVhYKFCHSkpKSkpK2swq/vjxYyIaMGCAkjIFZUI9A1CHJ0+eEFFtbS1bbGxslH61rq6OiKQLkqQapaenjxw5ctGiRUTEnhretGlTfn5+TEwMu0R55syZ1tZWGxub0tLS+/fvs1anTp0yMTE5ffq0ig5nwoQJdXV17KCkPX36lF4opdu3b7ezs2PnSe1RbkNvb28iSktLI6KioqLy8vLZs2d3GjM8PHz58uU5OTlE1NjY6O/vP3PmzNDQUOltKisriWjcuHEdpASagnoGoHINDQ2bN28mopKSkujo6MjISPZsk0gkqq2tjYmJYQMprVu3TlLnduzYUVVVVVFRUVpampGRwXpeREZGOjo6/l979x7WxJU2APwNUaiiyEUQ8bIELMUl1lv7KSrqIypdoVErGEHEK1oVKSgCVrRWjWKtXJ4Q14KI9VJv9bIsuLpSqrYYqK7W3RZItEgFAUUEuUSBhPn+OE/nSQEhhFyH9/eHT+Zk5swZA3k5Z86cNy4ubv369d7e3m5ubkuWLKmpqZHL5X5+fhYWFrdv3yaHm5mZWVhYmJmZaemKgoKCKIoSi8XKhdevXw8LCwOA4uLi/fv3379/n5QXFRUVFhZGRES8qTaNH7h27VqRSBQfHx8REREWFrZ9+/Z9+/Z1Wufw4cNv3rz53nvvLV68eP369atWrbpw4QK5nUnLyclhs9mqpyZHOqXn+ZU9D87XZwDo+nx91ZFOmJYq75TqP59z5swJCwtTsVqJRDJhwgQ12qP2gVqq88MPPwwODu50N5yvrxfYP0MIqSMtLe3y5cuqzPSTyWRCofDw4cNdPYXaB2qpzry8PKlUSq+/jAwNxjOEDEtDQwP9ryGzs7M7f/58eHi4TCbreM+ioqI9e/ZwudyunkLtA7VRZ3l5uUAgyMrKIk+4IwOE8QxpBWaNUkNDQ8PWrVvJnI7Q0NDc3Fx9t6gTXC5XIBCQ54473k29GKD2gRqvUy6XHzt27OTJkzrOYIC6BOMZ0ox2s0ap4siRI1wud8yYMUOHDiXHkmVkeyBzc3OBQEDuBKSmpk6cOFHfLeoch8PpCevz9urVKyoqCntmBs5wl6tB7dJ9jitVvClrVKfS0tJWrlx5+vRpPp8PAJcuXVq2bFlpaSm9g2FeL0LIAGE8Mya6z3Glog6yRnWM5Kn629/+RjbnzZuXnJxML15usNeLEDJAON5oNHSf40pFVGdZozrQ0tICAPHx8XTJggULyIR1g71ehJBhwnhmoO7cuTNx4sSQkJDt27f37t27oaFBOcdVS0vLjRs3wsPDORxOWVnZ9OnT//KXv9TU1Lx+/fqLL75YtWrV+++/P2vWrF9++YXU9uDBAz8/v+jo6KCgoKlTp/7vf/8DAJlMdvLkyYCAgMmTJ+fm5o4bN87R0TEnJ0cqlc6fP9/W1nbkyJEk/aXnRwAAIABJREFUKVfHOs4a1XEirg0bNgDAjh075s6dS2Z+s9nsefPmwZ9zehnU9SKEDJRen37riVR8XtXFxcXa2pq85vP5z549o5TyPDU2Nt66dYsswb53796srKxVq1bV19cHBwcXFhaSo2bPnj1o0KDa2lqKot5++21nZ2eKopqbmy0tLblcLkVRLS0tZBbigAEDMjMz8/PzAcDR0XH//v0vX74keZ6mT5+u+qW1mzWq00Rcx48fJ2uWW1tbHzp0SKFQ0G8Z7PWCNp+n1i983l8j8HlqvcD/cV1T8fvC1tYWABITE1taWn755RfyNQ1/zlv4zjvvAMCLFy/IZl5eXtu/VzIyMiiKiouLO3XqFEVRZKG/3r1705Uo10mSctFv2dnZWVpadvUCv/rqKwAYN24cXSKXyzs+5Pnz5+vWrSP5TXx8fOrr69u2zaCuV2N/TiJGU+VnCWkQzgcxUH//+9+XL1/+ySefHD9+PCkpqd2JwmTJcDoN1e3bt7lcLhlbayU8PLyhoeHgwYMvXrxobGxsbm5u96StzmJtbU3WZu2SVatWhYWFKWeN6jQRl42NjUgkWr16NY/Hy8jIiIyMbPeRJoO63rCwMHd3dxV3NiLkXmZ4eLi+G2LcxGJxQkKCvlvR42A8M1ALFiwYO3bsunXrrl696uHhkZKSsnTp0o4PqaqqKioqkslkdCpIAGhpaTExMbl9+zafzz948OC6detOnjyp1ZaTrFGkf9mxmzdv9u/ff+zYsWRz9OjR169fd3Z2Pn36dKeP6IK+r9fd3Z2Ri9KeO3cOABh5aTqG8Uz3cD6Igfrss8+cnJyuXLly6tSp5ubmmJgYaC/HlTJXV1eZTEavIw4ABQUFSUlJABAUFNTc3PzBBx/AH1MKtadt1qg3JeLq37//xo0bldvD4XAGDRpkZ2dHNo3iehFCBgL7Zwbqyy+/DA8Pt7S09PX1/fjjj8mdHjrHFclWTHKLNDQ0mJubA8DcuXOdnJx27txZWlrq6elZUFDw008/ffvttwBQXl5eW1t77dq1yspKkobxp59+cnBwGDhwIABQf9wQIuNy9fX1/fr1o+snPZ4Omrpz586qqqq1a9e6urq2zRqVmZm5aNGic+fOkeii7O23375+/frKlSuFQiE5Y0ZGRkVFBUmtYrDXixAyUPq+gdfjqDgfBADGjRsXGxu7ePFiHx+fR48eURS1ZcuWwYMHnz9/vqGhYefOneQTXL169b1798hRxcXFPB7P2tra3t5+9erVlZWVpFwkEg0YMOD//u//cnNzExMTrays5s6dW1BQsHHjRgAwMzPLysq6evUqmZoYGhpaVVUlFArJ/aovvvji+fPnHTQ1LS1tzJgx5ubmAQEBK1asSE9PV3732rVrDg4O2dnZ7R47ePBgALCxsZk1a9asWbMmTZp08eJF+l3DvF4K5zeizuD8Rr1gUThZS7fIQBy5S4GMFIvFOnPmDCNvMuHPp0acPXuWz+fjt6uO4bgKUgnrzSQSib5bhxBCeP8MqQb/0kQIGTjsnyGEtOXBgwd0NueysrK0tDQ+nz9p0iT1aqPvcdJSU1PHjh3bv3//MWPGpKWlKb+Vn58/b968gQMH2tra+vv7l5eX028dOXJk4cKFMTExwcHBp06dIoUKhSI6OvrJkyfqtQ0ZBD3fv+t58H47A4A254OUlJTosRIN/nxev349ICCgqamJLnn8+DH8ec0X1d2+fZs8aEiXREdHBwYGikSiTz75pE+fPgAgFArJW/n5+fPnz7948eK9e/eWLFkCAJ6enuStnTt3Ojo6VldXUxRVXV3t6OiYmJhI3nrx4sVHH31UVFSk3vUqw/kgeoH/47qG8YwBtBfPHj165OHhocdKNPXzmZ+fP3z48Kqqqlbl6sWz6urqrVu3kgXPSElJScnixYvpHa5evQoAI0aMIJuJiYkymYy8Jmt49uvXj6Kox48f9+7de+/evfSBAoGgb9++9IzW+/fvc7lcesU1tWE80wscb0TIUGgkRY4h5NmhKCowMHD58uXW1tYaqXD37t2RkZHKg42///47PZIJALNnz7a1tX327BnZDA0NJT02Qi6Xr1y5EgBOnDjR3Nzs6elJvzVjxgyZTJaamko23333XWdn556QcZuRMJ4hpBW1tbVRUVFbtmzZtGmTl5fXpk2byJPdKSkpJiYm5Ku5rq4uLi6O3lROkQMAubm5ERERHA7n6dOnvr6+NjY2o0aNunDhQpcqgc5S9mhDenr63bt32z5Brx6hULhw4UILCwvlwsmTJw8aNEi5pKmpycPDo+3h27dvT0hIIKtP/fjjjwCgnPGcPKp///59usTLyyslJYVOKouMib47iD0OjjcyAHQ23lhXV+fi4rJjxw6y+ezZMxcXFycnp5qaGoqinJ2dlX/1lDfhj+E4hUKRkZFBOhkbNmy4efPmN998QxZQzsnJUbESotOUPco08vPp7+/PYrGam5vbvgVdHG8Ui8VxcXHkNUn02u5uOTk5ffr0uXv3rnLhxYsXp06dCgAcDockMBozZgwAvHr1it5HJpMBgLu7O11CMgcpj0mqAccb9QL7ZwhpXmxsrFQqXbNmDdm0tbWNiYkpKioiS3n17t1beedWm4SJiYm3tzfpPcTGxnp4ePj7+5NEqUKhUMVKCB6PV1tb6+Pj092rUplYLB4wYABZfqU7Xrx4kZKSEhYW1vFuCoXi008/PXLkCL22NTF9+vRDhw4lJSU9ffp01apVX3/9NenkKY9bktdNTU10Cen2/fDDD91sPNI9jGcIaV5OTg78OR8N6SjcunWrS/WQlSTpBAI8Hg8AHjx40NX2dJqyR7MqKirotD7dsXbt2sDAQKlUKpFIJBJJY2MjAEgkklaDgZ9//rmnp+eiRYtaHW5paTly5Mj169eTnHzHjh0jPTwy8EtUV1cDgIODg/JRAECypSPjgs9TI6R5JA4VFxe7ubmREvJX/4ABA7pTLfnaJZ02Q8Zms9+UVKFL0tPTz54926rQ1dV1xIgRdFDPyMgwNzePiorqoJ65c+cCgKmpKfk4ysrK6Htv5Lm0KVOm0Du3esQNGRHsnyGkeaQ3lpmZSZeUlJQAwMyZM+HPY1wURb18+ZLereMUOVVVVepVopHoorrBgwcr94HUpnyji1K6f0YHs2vXrpWWlioHM7FY3LYeErTmzJmzZMkSS0vL77//nn4rOzvb1NQ0ICCALiE9Nnt7++63H+kYxjOENC8yMpLL5QqFwoqKClIiEokmT54cEhICAOR7effu3Q8fPkxMTCTDaFevXm1paaFT5CjXRkejrKys8ePHk9tyqleSmZlpaWl55coV3Vw7AEybNq2urq6+vr5V+atXr6BNcD1w4ICbm9vp06e7epbvvvsuNjZWoVCIRCKRSJSUlLRx48bLly8DQHx8/JEjR0iMb2xsjIqK4vP5ISEhVlZWW7ZsOXToEGlbXV1dcnJyTEyM8ozH58+fw597bMhY4HgjQprXp08fsVi8a9eupUuXjho1is1m29jYZGdnkykS+/btKysri4uLy8vLS0pKunDhgqOjY01NjVwu9/PzO3r06O3bt5UHFRMSEpYtW9bS0lJeXn7jxo2uVmJmZmZhYWFmZqazyw8KCkpNTRWLxbNmzaILr1+/ThaXKi4u3r9//+zZs0ePHg0ARUVFhYWFERERbW+AdUAsFvN4PJlMlp2dTReyWKyHDx8CQG1t7cGDB0mdpqamISEh9DNnkZGRAwcOXLdu3fDhw6VS6ebNm4ODg5VrzsnJYbPZjEyewHiYL0bXMB8HA+gsX8zIkSMLCwt1+UuqqZ9Pb29vFxeX+Ph4VXaWSqVBQUG5ubndPKlG8Hg8e3v75OTk7lSC+WL0AscbEUKal5aWdvnyZVVmCcpkMqFQePjwYR20qlN5eXlSqVR55RFkRDCeIWS4Ghoa6H+Ni52d3fnz58PDw8kDyx0gj+VxuVzdNKwD5eXlAoEgKytL+UELZEQwniFkiBoaGrZu3UrmdISGhhrIWFyXcLlcgUAgEok63c0Q4odcLj927NjJkyeV54Yg44LzQRAyRObm5gKBQCAQ6Lsh3cLhcIxlbd9evXp1/BAbMnzYP0MIIcQEGM8QQggxAcYzhBBCTIDxDCGEEBPgfBA9KC0tbbvKKjIu7a4TyAClpaUAgD+f3cTUHw8Dh+uD6Jqfn9+3336r71YghLQOv111DOMZQlqns/WxEOrJ8P4ZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJmBRFKXvNiDENGvWrJFIJPTm3bt3ORyOlZUV2WSz2V9//fXQoUP11DqEmKmXvhuAEAMNGjQoOTlZueS///0v/drJyQmDGUIah+ONCGleQEDAm94yNTVdtmyZDtuCUE+B440IaQWXy83Pz2/390sikbi4uOi+SQgxG/bPENKKoKAgNpvdqpDFYo0ePRqDGULagPEMIa3w9/dXKBStCtls9tKlS/XSHoQYD8cbEdKWSZMm5eXltbS00CUsFqukpGTIkCF6bBVCTIX9M4S0ZcmSJSwWi940MTGZMmUKBjOEtATjGULa4ufnp7zJYrGCgoL01RiEGA/jGULaMnDgQE9PT3pWCIvFmj9/vn6bhBCDYTxDSIsCAwPJLWo2m+3l5WVjY6PvFiHEWBjPENKijz76yNTUFAAoigoMDNR3cxBiMoxnCGmRubm5j48PAJiamn744Yf6bg5CTIbxDCHtWrx4MQDMnz/f3Nxc321BiMnw+TMjcPbsWT6fr+9WINRz+fr6njt3Tt+tQJ3A9fWNxpkzZ/TdBPQnYrE4ISFBlc/lxIkTixYt6tXLmH7d+Hx+WFiYu7u7vhuif/Hx8fpuAlKJMf2C9XALFy7UdxNQawkJCap8Ljwe76233tJBezSIz+e7u7vjTx0AYM/MWOD9M4S0zuiCGULGCOMZQgghJsB4hhBCiAkwniGEEGICjGcIIYSYAOMZQgghJsB4hpCuTZw4MTIyUt+t0KQHDx4cOHCAvC4rK0tLS+Pz+ZMmTVKvNqFQqJw3DgBSU1PHjh3bv3//MWPGpKWlKb+Vn58/b968gQMH2tra+vv7l5eX028dOXJk4cKFMTExwcHBp06dIoUKhSI6OvrJkyfqtQ0ZMnz+DCFd43A4Wp3BX1paOnToUO3V38qNGzeSk5OPHj1KNh0cHGbOnLlixQpXV1c1artz5050dLRyyZYtW0pLS4ODg6VSaXJy8ooVKxoaGkJCQgCgoKAgJiZm2bJlO3bsiIuLO378eGVlZVZWFgDs2rXryJEj9+7ds7S0rKmpGTt2bGVlZWhoKJvNjoqKWrVq1ZdffsnhcLp78cigUMjgkRUo9N0K1Jphfi6PHj3y8PDofj0AcObMmU53y8/PHz58eFVVVdvDXV1du3rS6urqrVu3vvPOO/R/bElJyeLFi+kdrl69CgAjRowgm4mJiTKZjLxubm62tLTs168fRVGPHz/u3bv33r176QMFAkHfvn2fP39ONu/fv8/lcuvr61Vpla+vr6+vb1evBekejjcixBxPnjzx8fGprKzUzekoigoMDFy+fLm1tbVGKty9e3dkZKTyYOPvv/9Oj2QCwOzZs21tbZ89e0Y2Q0ND+/TpQ78rl8tXrlwJACdOnGhubvb09KTfmjFjhkwmS01NJZvvvvuus7Pz5s2bNdJsZCAwniGkOy0tLefOnVu2bNm0adMAID09fc2aNcOGDaupqVm2bNnAgQNHjRr1n//8BwByc3MjIiI4HM7Tp099fX1tbGxGjRp14cIFAEhJSTExMSFf+nV1dXFxcfTm0aNHf/3114qKirVr15Izfv/998OGDbt586Y2Lic9Pf3u3bsffPCBRmoTCoULFy60sLBQLpw8efKgQYOUS5qamjw8PNoevn379oSEhISEBAD48ccfAUB50HXYsGEAcP/+fbrEy8srJSWlqKhII41HBkHfHUTUOcMc10LqfS6PHz+GP8biSktL+/XrBwACgeD3338/ceIEAEyYMEGhUGRkZJCex4YNG27evPnNN9/0798fAHJyciiKcnZ2Vj618ib8eaDvH//4R9++ff/5z392tZ2gwnijv78/i8Vqbm5u9/AujTeKxeK4uDjymtx4a3e3nJycPn363L17V7nw4sWLU6dOBQAOh3P48GGKosaMGQMAr169oveRyWQA4O7uTpfcu3cPAJTHJN8ExxuNBX5LGgGMZ4ZJ7c9F+bte+V4RRVGDBg0yMzMjr11cXACgoaGBbJKex6JFi6g23/jKm20DiVwuV6+RncYzR0dHS0vLNx2uejyrqqpasWJFS0sL2XxTPJPL5dOmTTt16lSr8urq6vz8/KSkpL59+wLA0aNHSXh7/fo1vc+rV68AYPz48XRJWVkZAMyZM6fT5mE8MxY43oiQPrWamG5lZdXY2Ehem5iYAAD5jgYAHo8HAA8ePOjqKdhsdndb+QYVFRVWVlbdr2ft2rWBgYFSqVQikUgkEvI/IJFIWg0Gfv75556enosWLWp1uKWl5ciRI9evX//VV18BwLFjx0hErKmpofeprq4GAAcHB+WjAODp06fdbz8yEDhfHyHjQL6LyX0gA8FmsxUKRffrSU9PP3v2bKtCV1fXESNG0PE7IyPD3Nw8Kiqqg3rmzp0LAKampm5ubgBQVlZG33sjz6VNmTKF3rnVXxKIAbB/hpBxqKqqAoCZM2fCH9/FTU1NAEBR1MuXL+ndWCyWXC5XPlAjIaddgwcPVu4DqU35RhelNN5IB7Nr166VlpYqBzOxWNy2HhK05syZs2TJEktLy++//55+Kzs729TUNCAggC4hPTZ7e/vutx8ZCIxnCOlUfX09ANTW1pLN169fK79bV1cHAMoBiY5GWVlZ48ePX7NmDQCQb/zdu3c/fPgwMTGRDNBdvXq1paXF2dm5vLy8pKSEHJWZmWlpaXnlyhVtXMu0adPq6urIFSkjN6taxdEDBw64ubmdPn26q2f57rvvYmNjFQqFSCQSiURJSUkbN268fPkyAMTHxx85coSE88bGxqioKD6fHxISYmVltWXLlkOHDpG21dXVJScnx8TEKM94fP78Ofy5x4aMHY43IqQ7Mplsz549AFBWVhYfH9/U1FRcXAwAAoFgw4YNaWlpZB2mbdu2ffbZZ+SQhISEZcuWtbS0lJeX37hxo1evXgCwb9++srKyuLi4vLy8pKSkCxcuODo61tTUyOVyPz+/o0eP3r59m4xMmpmZWVhYmJmZaeNygoKCUlNTxWLxrFmz6MLr16+TxaWKi4v3798/e/bs0aNHA0BRUVFhYWFERETbG2AdEIvFPB5PJpNlZ2fThSwW6+HDhwBQW1t78OBBUqepqWlISAj9zFlkZOTAgQPXrVs3fPhwqVS6efPm4OBg5ZpzcnLYbDYm4GYSFkVR+m4D6sTZs2f5fD5+UoZG25/LyJEjCwsL9fW5s1isM2fOdPp17+3t7eLiEh8fr0qdUqk0KCgoNzdXEw3sLh6PZ29vn5yc3Omefn5+AHDu3DntNwp1C443IoTUl5aWdvnyZVVmCcpkMqFQePjwYR20qlN5eXlSqVR55RHEABjPmEx5mgAyOg0NDfS/BsvOzu78+fPh4eHkgeUOFBUV7dmzh8vl6qZhHSgvLxcIBFlZWeQRdcQYGM8YqLGxcc+ePZMmTbKxsdF3WwA6TPbxJllZWXPmzGGxWCwWa8aMGTNmzHj//ffnzp2bmppKJvUxW0NDw9atW8mcjtDQUAMZoHsTLpcrEAhEIlGnuxlC/JDL5ceOHTt58qQuUxAg3cD7Z0ZAjfs0r1+/HjJkyIsXL/T++ZJkH+7u7iTZx6tXr4RCIUn20bGysrIhQ4ZwOBzyUC1FUZmZmWFhYSYmJpcuXfrrX/+q/bZ3gtn3NVW8f9YT4P0zY4H9M2Z666237Ozs9N0KKC0tLSkpOX78+Lp16xISEi5dugQAiYmJqhxLHh+mJ+axWCwfH58ffvihvr6ex+O1muaOEEIYz5AWdZzsQw2DBw/etWvXb7/9hnfyEUKtYDxjjlevXm3atGnNmjXbtm379NNPlecRvH79+osvvli1atX7778/a9asX375BTpMVgIAd+7cmThxYkhIyPbt23v37k1qa7eeDnSc7EO9VCa+vr5sNvvf//63fi8NIWRwdLr6MVKLKuu4y+XyCRMmBAcHk83ffvuNPHhLNoODg8mTTBRFzZ49e9CgQbW1tW9KVkJ2c3Fxsba2Jq/5fP6zZ8/eVI/qF9Iq2UenqUzgDWu0Dx482MbGRu+Xxuy8B6BafuqeANfXNxY4H8QIqDLvQCQShYSEFBQUkJWQAOCdd96RSqUURf30008TJkxotX9GRoa3t7erq6tEIqFrtre3r6mpIbem7OzsKisrExMTN2zYkJ+fP3z48IKCgjfVo8pVKBQKT0/Pjz/+WHl5CIVC0cHq7ywWy9XVtaCgoFX58OHDFQrFkydP9Htp5HMhUY15+Hx+WFiYu7u7vhuif/Hx8UOHDsX5IEZAr9EUqUSVfgBJJqK8riu9qGtSUhKXy233qA7SaH377bdkdvV7772Xm5vbcT2q2LZt286dO7t0CLTXP2tqajI1NSVpq/R7aUyNZKgt7J8ZBbx/xhBk3T+yBHsrVVVVRUVFrR53bWlp6bjCBQsW/Pzzz15eXnfu3PHw8Pj666/Vq4cgyT62bdumys4dy87ObmpqIsv0GcKl6ftXWFsAxxv/4Ovr27WfUaQnGM8YgvQ/MjMz231LJpPt27ePLikoKEhKSuq4ws8++8zJyenKlSunTp1qbm6OiYlRrx7oMNlHV1OZNDU1ffrpp2PHjg0NDTWES0MIGRB9/+mDOqfKeOPPP//cq1cvGxubK1eukMXILSwsAODRo0evX792cnICgBUrVpw8eTImJmb27NlksoOjo6NyzUOGDAGA5uZmiqL69u1bXV1NUVRzc/OAAQMmTJjQQT0dyMrKmjFjRtIfhEJheHh4TEwMRVEZGRn9+vX717/+1e6BpLfk6OhIl9y9e3fq1KkcDic/P5+U6PfScD5ID4HzQYwFY38bmUTF782bN29Onjy5f//+Tk5OsbGxU6dO/fjjj7/77juFQlFcXMzj8aytre3t7VevXl1ZWUlRFL1A0e7du1++fJmQkEA2o6OjSf6qcePGxcbGLl682MfH59GjRxRFtVtPB27dutW3b99Wf0KxWKzffvuNoqhr1645ODhkZ2e3PfDHH39cuXIl2X/69OleXl48Hm/BggUikai+vl55T31dmuqfi5HCeEbDeGYscH6jEWD2ukrGi9mfC653RcP1rowF3j9D3cV6M4lEou/WIYR6CsxPjbqLqR0UhJBxwf4ZQgghJsB4hhDSnQcPHtBrSZeVlaWlpfH5/EmTJqlXm1AoZLFY5LVCoYiOjiYPYqKeCeMZQgaqtLTUQCrRlBs3buzYsYM8OwgADg4OM2fOPHv2bHV1tRq13blzJzo6mt5ks9lRUVGhoaGPHj3STHORscF4hpAhKi4uDggIMIRKNKWgoCAoKEgoFPbu3ZsuHDZsmHq11dTUXLp0qdXhVlZWn332GY/HU04ugXoOjGcIGZwnT574+PhUVlbqvRJNoSgqMDBw+fLl1tbWGqlw9+7dkZGR9GAj7d1333V2dt68ebNGzoKMC8YzhLSrtrY2Kipqy5YtmzZt8vLy2rRpU01NDQCkpKSYmJiQb+S6urq4uDh68+jRo7/++mtFRcXatWsBIDc3NyIigsPhPH361NfX18bGZtSoURcuXOhSJaBuwjmNSE9Pv3v37gcffKCR2oRC4cKFC8kKOG15eXmlpKQUFRVp5FzImOj1aW6kEmavQ2G8VPlc6urqXFxcduzYQTafPXvm4uLi5ORUU1NDUZSzs7NyDcqb8EduAYVCkZGR0adPHwDYsGHDzZs3v/nmG5IfICcnR8VKiE4TzikDja4P4u/vz2KxyHpjbU/Ubpa7NxGLxXFxceR1qywKxL179wBg7969are2FVwfxFhg/wwhLYqNjZVKpWvWrCGbtra2MTExRUVFe/bsAQDlO0ltNwkTExNvb29yoyg2NtbDw8Pf33/Xrl0AIBQKVayE4PF4tbW1Pj4+3b2qrhOLxQMGDCA5ZrvjxYsXKSkpYWFhHexDUqL/8MMP3TwXMjoYzxDSopycHAAg3Sli6tSpAHDr1q0u1WNiYgIA9GKYJN3dgwcPutqeDrKnalVFRYWVlVX361m7dm1gYKBUKpVIJBKJpLGxEQAkEony6KKlpSUAPH36tPunQ8YF1wdBSItIHCouLnZzcyMlpPcwYMCA7lTr4OAA3ZgcqHtsNruruYHalZ6efvbs2VaFrq6uI0aMoKN720kiqIfA/hlCWkR6Y8p56UpKSgBg5syZ8Mc3b1NTEwBQFPXy5Ut6NxaLJZfL31QtSdyqRiUaCSpqGDx4MJkF003KGdgppftnyl1V8jSbvb1990+HjAvGM4S0KDIyksvlCoXCiooKUiISiSZPnhwSEgJ/ZGHdvXv3w4cPExMTyejZ1atXW1panJ2dy8vLSfCj0dEoKytr/Pjx5Lac6pVkZmZaWlpeuXJFN9eubNq0aXV1dfX19a3KSfqeVlH2wIEDbm5up0+fVu9cz58/B4ApU6aodzgyXhjPENKiPn36iMXigICApUuXRkREREVF2djYZGdnk5kR+/btmzBhQlxm7gl7AAAB3ElEQVRc3Pr16729vd3c3JYsWVJTUyOXy/38/CwsLG7fvq1cW0JCQlVVVWVlZXl5+Y0bN7paiZmZmYWFhZmZme7/H4KCgiiKovOSE9evXyczO4qLi/fv33///n1SXlRUVFhYGBERod65cnJy2Gw2ZrrpgTD/mRFgdp4t46XLz2XkyJGFhYW6/BnQeP4zb29vFxeX+Ph4VXaWSqVBQUG5ublqnIjH49nb2ycnJ6txbLsw/5mxwP4ZQkgX0tLSLl++rMq0Q5lMJhQKDx8+rMZZ8vLypFIpveQx6lEwniFkBMiChEa9LKGdnd358+fDw8NlMlnHe5Ln87hcbldPUV5eLhAIsrKylB+QQD0HxjOEDFpDQ8PWrVvJnI7Q0FD1huAMBJfLFQgEIpGo093UCEhyufzYsWMnT54cOnSoug1Exg2fP0PIoJmbmwsEAoFAoO+GaAaHw9HSYsG9evWKiorSRs3IWGD/DCGEEBNgPEMIIcQEGM8QQggxAcYzhBBCTIDzQYwGeagTGY7S0lJg9OcSHx+PDxEDQG5u7sSJE/XdCtQ5XB/ECJAEhvpuBUI9l7u7+8aNG/XdCtQJjGcIIYSYAO+fIYQQYgKMZwghhJgA4xlCCCEmwHiGEEKICf4fk4imnrN1qO8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "\u003cIPython.core.display.Image object\u003e"
            ]
          },
          "execution_count": 246,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.keras.utils.plot_model(\n",
        "    model_stream,\n",
        "    show_shapes=True,\n",
        "    show_layer_names=True,\n",
        "    expand_nested=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7NOG8wrYpnnq"
      },
      "outputs": [],
      "source": [
        "\n",
        "sream_predicted_labels = []\n",
        "for input_data in train_data: # loop over all audio sequences\n",
        "  \n",
        "  # add batch dim - it is always 1 for streaming inference mode\n",
        "  input_data = np.expand_dims(input_data, axis=0)\n",
        "\n",
        "  #   output_predictions = []\n",
        "  #   output_ids = []\n",
        "  # run streaming inference on one audio sequence\n",
        "  start = 0\n",
        "  end = flags.window_stride_samples\n",
        "  while end \u003c= input_data.shape[1]: # loop over one audio sequence sample by sample\n",
        "    stream_update = input_data[:, start:end]\n",
        "\n",
        "    # get new frame from stream of data\n",
        "    stream_output_prediction = model_stream.predict(stream_update)\n",
        "    stream_output_arg = np.argmax(stream_output_prediction)\n",
        "    #     output_predictions.append(stream_output_prediction[0][stream_output_arg])\n",
        "    #     output_ids.append(stream_output_arg)\n",
        "\n",
        "    # update indexes of streamed updates\n",
        "    start = end\n",
        "    end = start + flags.window_stride_samples\n",
        "\n",
        "  sream_predicted_labels.append(stream_output_arg)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "igcc_5eHh01s",
        "outputId": "aa7d166e-fefe-48ee-9ca8-d1d493e5da5a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "accuracy 93.5546875\n"
          ]
        }
      ],
      "source": [
        "# validate that accuracy in streaming mode is the same with accuracy in non streaming mode\n",
        "stream_accuracy_internal_state = np.sum(sream_predicted_labels==train_label)/len(train_label)\n",
        "print(\"accuracy \" + str(stream_accuracy_internal_state * 100))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F5WYgOtSqrQb"
      },
      "source": [
        "### TF Run streaming inference with external state"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2hTLEY1qq_ig"
      },
      "outputs": [],
      "source": [
        "# convert model to streaming mode\n",
        "flags.batch_size = inference_batch_size  # set batch size\n",
        "\n",
        "model_stream = utils.to_streaming_inference(model_non_stream_batch, flags, Modes.STREAM_EXTERNAL_STATE_INFERENCE)\n",
        "#model_stream.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AyeABeg9Mbf6",
        "outputId": "9031e48a-44b2-4826-f7ad-115d7542ebee"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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fda+srCzbf729vd1cmrJVv359ffTRR3rmmWf01ltvqWbNmg4tt3v3br388suqVatWqctQlnm5Ot7BgwcVGRmp9evXu6z8QH67du1S69at3V0M4JJ2KbcDJOnPP//U2LFj1bhxYz344INq06ZNhWgfXOrxCmtDJCUlaeXKlTp27Jj++OOPUscAAAAlx5OeAFCM3NxcRUVF6dZbb1XdunVdGnvmzJnq1q2by+NWJDt27FBERIT69++vpUuX2k3r3LmzJk2aVO5lcFWcoixatEjXXXedatWqpWuvvVaLFy92Oo+xY8fqiiuukMViUZUqVXTfffepd+/e6tSpk3r37q0PP/ywHEpuz5H9OT4+Xtdee60sFovat2+vU6dO2U3/8ssv1bt3b1ksFnXq1Enx8fHlXewSY991n6ysLD333HPat2+fJGnMmDEue3WaK7Vv316RkZGKjY11apmyusBYlnm5Ml5OTo7effddvf/++/L39y+DkgEXFxMTI4vFYvcvOjq6wHxJSUny8vJSamqqpMv3GO4K//nPfxQeHm7bHo899phWrVrl7mJpw4YN6t+/v61cI0aM0ObNm91drErncmgHGGNkjFF0dLTCwsLUpk0b2zR3tw8u5XhFtSHatGmjsLAwRUVFKS8vj1fUAgDgRnzTE8Bly5lvp5w+fVpNmjTRsWPHSt2B2b9/v8MXWc+cOaMmTZooLS3tsu44nTlzRtWrVy/w3ZoBAwaoTZs2ioiIKLNYhW2f8ojjqPDwcO3fv19dunRRYmKiFixYoFOnTmnevHl6+umnncrr0KFDatSoka688krt3LlTknT27FmFhYVp7ty5mjlzpsaPH+9UnuWxP2dkZMjHx0eSNGzYML355pt20/fs2aPmzZtr586duvLKK50qr6tdzvuuxLeJHMW3ECsfvulZUFnvx86cXyqynJwcdevWTYGBgbY0Ly8vhYSEqF69enbzRkREaNOmTVq7dq0k9x/Dy2MblCTP8twXmjdvrj179ig7O1s1atQolxjFuXD9Tp06pZo1a+rvf/+7kpOT3VKmskI7wDG0AyDxewEAoIys4PW2AOCA6tWrq379+jp27Fip8klOTlZISIi++eYbh+avVq2a6tWrp7S0tFLFreyqVatWaPry5cvLNE5R26es4zhq//792rdvn9577z1b2j333KNevXopOjra6UHPhg0bSpI8PP560UPVqlX16quv6s0339T8+fOdGvQsr/3Z+urb2267TQsWLNAdd9xhdxGoSZMmkqQWLVo4XFZ3uVz3XQAoDWfPLxXZ8uXLNWjQII0cObLYeZctW6bJkyfbLesu5bENSpJnee8L1oFOdw14FrZ+7i4TAAAAUJkx6AkALnLgwAH16dNHubm57i4KClERt8+ePXs0a9Ysu7SePXuqXr16tlfflQUvLy/VqlVLGRkZDi/jivqKi4vT9ddfr6FDh6pTp062QU4vr/PNlypVqpRb7MqkIu67AFBSl9IxzRijqKgo7d27Vx9//LG6dOmixx9/XM2bNy8w748//qjk5GQ98MADri/oBcpjG5Qkz0tpXyjMpb5+AAAAgDvwTU8AcNKuXbsUGBgoPz8/3XjjjdqwYYNtWlJSkvr166fJkycrJCREt912m3755RdJ0pIlS/Tbb7/p0KFDdnf7Z2Vladq0aXr00Uc1duxYde/evdDvPB05ckRBQUGqW7eu2rdvrx9++MHhMq9atUrDhw9X06ZNlZ6ersGDB+uKK65Qhw4d9N///tc2X0ZGhsLCwhQeHq7x48erV69eGj9+vNLT05WXl6eNGzfqmWeeUYsWLZSSkqLu3bvr73//u1JSUvT+++/rkUceUdeuXZWQkKDrr79ezZs316ZNm5SYmKgHHnhA9erVU9u2be1iFldvhcnLy9OKFSs0ePBgdevWzZbu5+enhx9+WM8884yeeeYZNWzYUJ6envr+++9LtH2KinOxenKmvovTtWtXNWjQoED62bNndeutt9r+/vrrr9W0adMSPwXx4YcfKjU1VU888YRdurv354YNGyo+Pl7Z2dkKDg7WuXPnilwH9t2Kte8CQHF++OEHde7cWU8//bSmTp2qKlWqKCsrq8Ax7WLH8PT0dJ0+fVqvvPKKhgwZok6dOumuu+7Sr7/+aotzseNndnZ2qc4BxcnIyFCvXr3UuXNnbdmyRREREQoICNBLL71UYN7ly5frnnvukY+PT6HHcEeOzwkJCZowYYJatGihw4cP286zHTp00MqVKyVJCxculIeHhywWiyQpMzNTs2fPtksr6hxfltvVke1T1DLFbfPStIsqSz07Un/vv/++vL29ZbFYFBUVZRtcXbZsmapVq6Z33nnnovVZ3G8PAAAAqJAMAFymJJm4uDiH5w8ICDCSTGhoqFm3bp158803jbe3t/H09DQ///yzMcaYNm3amFatWhljjDl37pypU6eOad++vV3MgIAA29/nzp0z3bt3N48++qjJy8szxhizePFiI8l8+umndnFfeOEFk5ycbFavXm0kmS5dujhc9v3795u//e1vRpKJjIw0e/bsMe+9956RZG666SZjjDGZmZnmyiuvNC+++KJtudTUVHPllVeali1bmtTUVLN582ZTs2ZNI8lMnz7drF+/3gwZMsRkZmaaXbt2GUnGx8fHrF692vz+++9GkmnevLl59dVXzYkTJ8y2bduMJNO9e3e78hVXb4XV3d69e+3ScnJy7Mr++eefG0kmLCzM4TgXxigsTnH1lJ6e7lB9l9SmTZtMjRo1zI8//mhL+9e//mVq1qxp22cuxrqNBg8ebAYNGmRuvvlm4+vraxYsWGDbB63cuT/nb6LMmTPHSDITJkwodDr7bsXdd+Pi4uy2FQrn7PkI7hcUFGSCgoLcXYwKxdn9+MorrzR+fn62v4ODg01qaqotL+ux68yZM0Uew0+ePGmGDh1qduzYYcunZ8+epkGDBiYjI8MYc/HjZ15eXqnOAc44ceKEiYyMNF5eXkaSeeutt2zT8vLyjL+/v4mPj7elXXgML+74nJubaz777DNTo0YNI8mMHj3afPPNN2bZsmWmVq1aRpLZtGmTMcaYVq1aFTg2X5hW2HnFEY5uV6uSnN+K2+bOtIus7RKrilLPjtZ/cfU3ZcoUI8n89ttvtrS9e/eaBx54wPZ3UfV59OjRi/72HEE7wDG0A2AMvxcAAMpIvMUYvpAN4PJksVgUFxdn963Ai2nbtq127NihjIwM1apVS5L02muvaezYsXrssce0ZMkSzZkzR40aNdLDDz8sY4zatGmjvXv36uzZs7aYAQEB2r59uyRpzpw5GjdunHbu3Kkrr7xSkpSbm6ulS5eqb9++qlOnji1uXl6e7c7wK664QqdOnVJWVpbD6xsQEKCdO3cq/2G/YcOGtqckpkyZosjISB08eND27UdJWrp0qUJCQjRp0iRFRUXZ8jl27Jh8fX0L1Gn+9fP399eBAwfsYjZo0EBnz57V8ePHbWnF1VtheReWdvr0aVWvXl3p6elq3769/Pz89MMPP6hq1aoOxSksxoXpztZTUfVdErm5ubrjjjs0YsQIPfzwwwWmeXp6FpuHxWJR69at9eWXXyo7O1v79u3Txx9/rMWLF+upp57SK6+8Yvvmpzv3Z4vFYld3wcHBWrFihT777DPdc889dtPZdyvuvhsfH6/g4GAFBQU5tdzl5sMPP1Tnzp3l7+/v7qLAQQkJCercubNWrFjh7qJUGM62q+rXr68jR44oOjpao0eP1u+//65mzZqpVq1ahR7TCjuGf/fdd7rpppsKzf+zzz7TvffeW6LjtKPngJJYsGCBhg8fruuvv9725ODGjRvVp08fpaam2n3H8cJyOXJ8vuqqq5SYmKisrCzVrFlTkhQdHa3Q0FA9/PDDWr58ue1cnD+fC9OKOq8Ux9nt6uz5zZFtLjneLiqsLipCPTta/8XV37Fjx9S8eXM9/PDDWrBggSRpxowZ6tChg+69916H6vNi7afi0A5wDO0ASNL+/fuVkJAgLtMCAFAqK/imJwA4yTrgKUl9+/bV2LFj9fvvv0uSnnnmGWVlZWn+/Pk6duyYzpw5c9FXclpfjZu/g+vp6anBgwcXmNc6QCRJ9erV044dO5wqd/7lrXx9fXX48GFJ0qZNmyTZr58k3XbbbZKkzZs32+XjyEWPC/OSzr/G88KyO1tvRalevbokacyYMTpy5IhWr15tGzQqqzjO1lN++eu7JP75z3/qjjvuKDDgKcmhC3tWXl5eatasmaTzF/buuusuXX311Ro9erTq1aunsLAwSRVrf160aJF++eUXDR48WP/73//sprHvOsad+y4AXOj111/X448/rrFjx2rp0qWKiYkp9NhrVdgx/Pvvv1f79u0v+lrxkhw/HT0HlMSQIUMUGhqqxMREW9ry5cvVt29fuwHPwjhyfLbeuGQdiJOkwMBAhYaGKmF2qSgAACAASURBVCkpqbTFL5az29XZ7ePINpecaxddqDLUs1Vx9efn56fRo0dr5syZevHFF9W4cWN9+eWXmjhxoiTH6tOZ9hMAAADgbgx6AkApWL+3aB1A+v777xUcHKz58+dr1KhRev/99y+6vPXiSVJSkq655pryLWwxrBdvkpOT1a5dO1u6dR19fHzKLbaz9XYxn3zyiZYuXarp06cXqNOyiOOuevrss8/k7e1tG5Asa/369dPo0aP1r3/9yxajIu3Pf/vb37Ry5Up16tRJgwYNspvGvusYd9YTT8NdnMVi0TPPPOPwE3Jwv379+rm7CJXeQw89pOuuu06jRo3S2rVrdeutt2rhwoV67LHHHM4jLS1Nu3fvVnZ2tt3gk3T+28YeHh5lepwuCx4eHvLz81O9evUkSefOndOHH36od999t9xiNm7cWJLUtGnTcoth5ex2dXb7OLLN3cWV9XzkyBH5+vpq27ZtxdbfuHHj9Nprr2nu3LkKDg7WjTfeaBsUdlV90g64ONoBkP56MhoAAJSO+3oEAHAJ2LdvnySpT58+kqSQkBCdO3dOvXv3lnT+YkF+FotFOTk5tr+tAxuRkZF2r7HZs2eP/v3vf5dr2S9kfdpr9erVdunWdbzzzjvLLXZx9eaoo0ePavjw4erSpYvtDnZJ+umnnxyKc+H2KYw76mndunXav39/gQHPLVu22P4/Nze3VDGsA5aNGjWypblrf7bGuTBeQECA3n77bX399dd26ey7FXffBYCivPDCC2rZsqU+//xzLV++XOfOndOUKVMkOXZMk86fF7KzsxUVFWWXvn37dsXExEgqu+N0WUlJSVFKSopt4Hzt2rWSpLvuuqvcYqalpUn66zhvfXLP+gpUY4xOnDhht4yj2+BCzm5XZ89vjmxzqfTtopJwZT2PGjVKnp6eDu3fdevW1ciRI/XGG2/otdde0xNPPGGb5mh9AgAAAJUFg54A4CDrhYsLv+d3//33217fefDgQR04cEDr1q3TsmXLlJ6eLun894f279+vVq1a6eDBg7ZBhsmTJ8vb21srVqzQnXfeqfnz52vq1KmaPn267eJFRkaGJCkzM9MW13rBxJlvehb2LT5rnjk5OZo0aZLat2+vefPm6dChQ7Z5YmNj1bVrVz399NN2+VwY25qef7DL+nqtkydPFpgv/0WZ4urt1KlTBdbBmqe1fiRpxIgRysrK0rvvvmu7g/348eP64IMPHIpz4fYpLI6z9VRUfTvqyy+/1IwZM5Sbm6vY2FjFxsYqJiZG48aN05o1aySdH8SqU6eOPv/884vmZS1Tdna2XXpqaqpGjhypqlWravLkybZ0d+3PqampklTo61T79eunZ555xi6Nfbdi7rsAcDEzZ860HcuCgoLk4+OjJk2aSFKhx7TCjuH333+/WrZsqYiICD355JNatmyZnn/+eYWGhurxxx+XVPzxszTngOJERERo7Nixttfinj59WiNHjlTfvn1t59vly5crKChIVapUsVu2sHOFM8fn/IN+69evV8eOHTV8+HBJ5we6JGnatGnatWuXoqOjdebMGUnnB2Hz8vIK3QaOcHa7Ont+c2SbO9oukv5qE+VvG7m7ng8ePGiLeeG3/TIyMjR8+HBVr15dFoul2PqzGj9+vM6ePau9e/eqVatWtnRH6rOo9hMAAABQIRkAuExJMnFxcQ7Pv27dOnPfffeZ7t27m2HDhpkxY8aY2NhYk5uba5snNjbW+Pj4mBtvvNEkJCSY6Oho4+vra+6//36TlpZmwsPDTaNGjcxHH31kW+aXX34xvXr1Mr6+vqZJkyYmNDTUnDhxwuTl5ZlXX33VSDKSTGhoqDl58qR55ZVXbGnjx483Z86cKbbssbGxtmWmTZtmTpw4YebOnWtLmzx5sjl16pTJzMw0kyZNMj179jTjx483kyZNMhEREebMmTMmKyvLRERE2JYZNmyY2bZtmzHGmMOHD5tx48YZSaZatWpm/fr1Zu3atcbLy8tIMmPGjDFpaWlm3rx5xmKxGEnmlVdeMUePHi223n744QczZswYW9y5c+eaAwcOmPDwcFva7NmzzeLFi40k0759exMaGmpCQ0PNk08+aVq3bm1mz55dou2TlZVVIE5GRsZF68mZ+i7O5s2bTc2aNW3L5f9nsVjMH3/8Yds3GzdubL766qsi8/roo49MUFCQbfmbbrrJ9O7d29x8882mbdu2ZsCAAebXX38tsN+4en/+4IMPzD333GMkmT59+phvv/22wLqcO3fO3HLLLXZp7LsVa9+1iouLMzQ3i+fs+QjuFxQUZIKCgtxdjArF2f1Ykrn++uvNjBkzzMCBA02fPn3Mn3/+aYwxdse0ix3DjTEmOTnZBAYGGj8/P9OwYUMzbNgwc+TIEdv0ix0/t2/fXqpzQHEWL15srr32WuPt7W0eeeQR88QTT5hVq1bZpmdlZRlvb2+zYcMGu+UKO4bPmDHDoeNzQECAkWRmzpxpjh49alJTU82MGTPMyZMnbfknJiaam266yXh7e5uePXuaxMREc+utt5pHH33UfPDBB+bMmTOFnuPLcrs6sn2KamsUt80daRd9++23ZvLkybb6GzhwoPnXv/7l8HmwvOr5q6++Mvfff78tXkBAgLn99tvN7bffbq666ipTrVo1I8m88847DtVffn369DFLly4tUBdF1Wdxvz1H0A5wDO0AGMPvBQCAMhJvMeaCWwcB4DJhsVgUFxfHt1MAoJxYv01Ec/PiOB9VPtZXk/Kdur+wH1cMbdu21Y4dOzjulrPKVs/Z2dm65ppr9PPPP6tGjRoui0s7wDEcPyHxewEAoIys4PW2AFDJWSyWYv/t3LnT3cXEBdhuAABUXpfbefxyW99LTWxsrEaPHu3SAU8AAADAHbzcXQAAQOlwJ2jlxHYDANfatWuXWrdu7e5i4BJRUc/j1u8uZmVlydvbu8zyrajr6y7lVc9laevWrRo2bJiys7OVm5tr+7YsAOfRhgAAoPLgSU8AAACgkkpKStKsWbNsf6ekpGjx4sUKDg7WzTffXKq8XZ3X0qVLFRgYqPDwcPXo0UOjRo1Senp6ieLFxMQUeAotOjpakpSbm6vJkyfrwIEDJV4foKLJysrSc889p3379kmSxowZo4SEBDeX6tJTmerZ29tbGRkZ8vDw0LJly1S1alV3FwllyGKxyNPTU2FhYYqKilJSUpLd9PJsH+Q3b948WSwWu7Tu3bsX+UT4H3/84XSMytCGSEpKUlRUlMaMGWNbBgAAuAff9ARw2eLbKQBQvtz9baL9+/fL39+/wudd0vPRxo0btWDBAi1ZskRVqlSxpe/bt0/NmjVTQECAtm/fXqqyuSqvN998UyNGjNCaNWt099136/fff1e7du3Ut29fffzxx07FycnJUbdu3RQYGGhL8/LyUkhIiOrVqydJOn78uIYMGaKZM2eqRYsWTq8L3/QsiHYVgAvRDnBMSY6fFotFrVu3LjDYKbmmfSBJP/zwg7p166bs7GzbNt6+fbsGDhyogQMH6oorrrDNu3XrVm3atEk//fRTiWJVpjZEixYtlJyc7PR+7+7fCwAAl4gVvN4WAAAAl5zk5GSFhITom2++qVR5O2r79u0KCQnRtm3b7C5oSlLTpk3LLI6r8nr33XclSZ06dZIkXX311apfv76+/PJLp+MsX75cgwYN0siRI4ucx9fXVy+88IICAwOVkJBQYV9PCQAomUu9HSCdH4y7kKvaB+np6frkk0/UtGlTu+/5/vzzz1q3bp3q1q1rN//GjRttNwyVRGVqQ1SvXt3puAAAoOzwelsAAABcUg4cOKA+ffroyJEjlSpvRxljNGjQID3++OPy8/NzWznKknU9NmzYIOn8KyTT0tLUo0cPp/IxxigqKkphYWHq2bOnXnjhBSUnJxc67z/+8Q+1atVKEydOLE3RAQAVzKXeDiiKK9sH06ZN06RJkwq8xjU4OLjAgOfZs2f18ccfKygoqFzKQhsCAADkx6AnAAAAKoyMjAyFhYUpPDxc48ePV69evTR+/Hjbd5kWLlwoDw8P20W2zMxMzZ492y5tyZIl+u2333To0CHbnfoJCQmaMGGCWrRoocOHDysoKEh169ZVhw4dtHLlylLlLUlff/21mjZt6pKnPlatWqUff/xRvXv3LvdYrjJnzhy1atVKoaGh2rt3r2JiYjRx4kQtW7bMqXwyMjLUq1cvde7cWVu2bFFERIQCAgL00ksvFTp/r169tHDhQu3evbssVgMAUEq0A0rOVe2DefPmqX///qpdu7ZD869du1b+/v4KCAgol/LQhgAAAPkx6AkAAIAK4eTJk+rUqZNq1qyp6dOna9asWXrvvff02WefqWPHjjpx4oSGDh2qli1b2papVauWxo0bZ5f23HPPSZIaNmyo119/XXl5eUpLS9P8+fOVnJysyMhIjR07VjExMdqzZ48eeughbd68uUR5W2VmZurYsWPKyMgot/qxiouLk8Vi0Q033FDusVyldevWSkhIUPPmzdW1a1elpqZq+vTpqlmzplP5+Pj4aNasWfriiy904MABRUZGKjc3V1OnTtWiRYsKzN+lSxfl5OQoPj6+rFYFAFBCtANKxxXtg4SEBOXk5OjGG290qlylebVtcWhDAACA/Bj0BAAAQIUwY8YMJSYmavjw4ba0evXqacqUKdq9e7defvllSSrwjaqi0qw8PDx077332r4HNWPGDN16660aMGCA7e79efPmlShvq8DAQGVkZKhPnz7FzltaW7ZskY+PT6Hf8qrMsrOz5evrqw4dOmj27NmaNGmSjDElzq927dp69tlnFRsbK0maP39+gXkaNGggSfr2229LHAcAUDZoB5ROebcPjh07poULFyo0NNThZU6fPq1Vq1aV66CnRBsCAAD8hUFPAAAAVAibNm2SdP7Jivxuu+02SdLmzZtLlb+Hx/mmb/47/wMDAyVJSUlJpcpbkjw9PUudhyMOHTokX19fl8Ryle+++04dO3bUY489pk8++URdu3bVq6++qqlTp5Y67yFDhqhGjRpKTEwsMK1OnTqSpMOHD5c6DgCgdGgHlE55tw9GjhypQYMGKTExUTt37tTOnTt15swZSdLOnTsLfc3r6tWr1axZM7Vt27bcykUbAgAA5MegJwAAACoE68XI5ORku3TrnfQ+Pj5lHrNx48aSZHv6ozLw9PRUbm6uu4tRpsLDw3X06FF1795dVatW1QcffCBJWrBgQanz9vDwkJ+fn1q3bl1gmvUbbQAA96MdUDrl3T5YtWqVevTooYCAANu/P//8U5IUEBCgXr16FVgmLi5OQUFB5VYmiTYEAACwx6AnAAAAKgTrkxyrV6+2S9+3b58k6c4775T010Wms2fPSpKMMTpx4oTdMhaLRTk5OcXGTEtLK7O8XTUQ2ahRI6Wnp7sklqtY67tq1aqSJH9/fzVo0KBMLiimpKQoJSWl0FfrHT9+XNL5b7MBANyLdkDplHf74NSpUzLG2P0LCAiQdL6eLnxa9v/Yu/P4GM/9/+PvSUKQErGLNbaGUKe0RWmp09J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            "text/plain": [
              "\u003cIPython.core.display.Image object\u003e"
            ]
          },
          "execution_count": 250,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "tf.keras.utils.plot_model(\n",
        "    model_stream,\n",
        "    show_shapes=True,\n",
        "    show_layer_names=True,\n",
        "    expand_nested=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RISdLTnmqrcA"
      },
      "outputs": [],
      "source": [
        "sream_external_state_predicted_labels = []\n",
        "for input_data in train_data: # loop over all audio sequences\n",
        "  \n",
        "  # add batch dim - it is always 1 for streaming inference mode\n",
        "  input_data = np.expand_dims(input_data, axis=0)\n",
        "  \n",
        "  # output_predictions = []\n",
        "  # output_ids = []\n",
        "  inputs = []\n",
        "  for s in range(len(model_stream.inputs)):\n",
        "    inputs.append(np.zeros(model_stream.inputs[s].shape, dtype=np.float32))\n",
        "\n",
        "  reset_state = True\n",
        "\n",
        "  if reset_state:\n",
        "    for s in range(len(model_stream.inputs)):\n",
        "      inputs[s] = np.zeros(model_stream.inputs[s].shape, dtype=np.float32)\n",
        "\n",
        "  start = 0\n",
        "  end = flags.window_stride_samples\n",
        "  while end \u003c= input_data.shape[1]:\n",
        "    # get new frame from stream of data\n",
        "    stream_update = input_data[:, start:end]\n",
        "\n",
        "    # update indexes of streamed updates\n",
        "    start = end\n",
        "    end = start + flags.window_stride_samples\n",
        "\n",
        "    # set input audio data (by default input data at index 0)\n",
        "    inputs[0] = stream_update\n",
        "\n",
        "    # run inference\n",
        "    outputs = model_stream.predict(inputs)\n",
        "\n",
        "    # get output states and set it back to input states\n",
        "    # which will be fed in the next inference cycle\n",
        "    for s in range(1, len(model_stream.inputs)):\n",
        "      inputs[s] = outputs[s]\n",
        "\n",
        "    stream_output_arg = np.argmax(outputs[0])\n",
        "\n",
        "    # output_predictions.append(outputs[0][0][stream_output_arg])\n",
        "    # output_ids.append(stream_output_arg)  \n",
        "    \n",
        "  sream_external_state_predicted_labels.append(stream_output_arg)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2Jh3O1eWh014",
        "outputId": "f4611ac2-20af-43ab-ce36-7b770e545055"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "accuracy 93.5546875\n"
          ]
        }
      ],
      "source": [
        "# validate that accuracy in streaming mode with external states is the same with accuracy in non streaming mode\n",
        "stream_accuracy_external_state = np.sum(sream_external_state_predicted_labels==train_label)/len(train_label)\n",
        "print(\"accuracy \" + str(stream_accuracy_external_state * 100))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KAJs5dBXsYCa"
      },
      "source": [
        "## Run inference with TFlite"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z5qmO5KrU7NP"
      },
      "source": [
        "### Run non streaming inference with TFLite"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "88bclN4rtu-5"
      },
      "outputs": [],
      "source": [
        "# path = os.path.join(train_dir, 'tflite_non_stream')\n",
        "# tflite_model_name = 'non_stream.tflite'\n",
        "\n",
        "tflite_non_streaming_model = utils.model_to_tflite(sess, model_non_stream, flags, Modes.NON_STREAM_INFERENCE)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VZgH11_0u2ZN"
      },
      "outputs": [],
      "source": [
        "# prepare TFLite interpreter\n",
        "# with tf.io.gfile.Open(os.path.join(path, tflite_model_name), 'rb') as f:\n",
        "#   model_content = f.read()\n",
        "\n",
        "interpreter = tf.lite.Interpreter(model_content=tflite_non_streaming_model)\n",
        "interpreter.allocate_tensors()\n",
        "\n",
        "input_details = interpreter.get_input_details()\n",
        "output_details = interpreter.get_output_details()\n",
        "\n",
        "inputs = []\n",
        "for s in range(len(input_details)):\n",
        "  inputs.append(np.zeros(input_details[s]['shape'], dtype=np.float32))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3J2n7VB5JxV6"
      },
      "outputs": [],
      "source": [
        "padded_input = np.zeros((1, 16000), dtype=np.float32)\n",
        "padded_input[:, :input_data.shape[1]] = input_data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TXqHxLcVregL"
      },
      "outputs": [],
      "source": [
        "non_sream_tflite_predicted_labels = []\n",
        "for input_data in train_data: # loop over all audio sequences\n",
        "  \n",
        "  # add batch dim - it is always 1 for streaming inference mode\n",
        "  input_data = np.expand_dims(input_data, axis=0)\n",
        "  \n",
        "  # set input audio data (by default input data at index 0)\n",
        "  interpreter.set_tensor(input_details[0]['index'], input_data.astype(np.float32))\n",
        "\n",
        "  # run inference\n",
        "  interpreter.invoke()\n",
        "\n",
        "  # get output: classification\n",
        "  out_tflite = interpreter.get_tensor(output_details[0]['index'])\n",
        "\n",
        "  out_tflite_argmax = np.argmax(out_tflite)\n",
        "\n",
        "  non_sream_tflite_predicted_labels.append(out_tflite_argmax)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KbIB3zaiKEru",
        "outputId": "4b4246fa-c02b-42d3-b7f3-39bafb7bfe11"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "accuracy 93.5546875\n"
          ]
        }
      ],
      "source": [
        "# validate that accuracy in TFLite is the same with TF\n",
        "non_stream_accuracy_tflite = np.sum(non_sream_tflite_predicted_labels==train_label)/len(train_label)\n",
        "print(\"accuracy \" + str(non_stream_accuracy_tflite * 100))\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xNaUWgivuatL"
      },
      "source": [
        "### Run streaming inference with TFLite"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "csQWZo4BuqEB"
      },
      "outputs": [],
      "source": [
        "# path = os.path.join(train_dir, 'tflite_stream_state_external')\n",
        "# tflite_model_name = 'stream_state_external.tflite'\n",
        "\n",
        "tflite_streaming_model = utils.model_to_tflite(sess, model_non_stream, flags, Modes.STREAM_EXTERNAL_STATE_INFERENCE)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "a4wAZqYouyob"
      },
      "outputs": [],
      "source": [
        "# with tf.io.gfile.Open(os.path.join(path, tflite_model_name), 'rb') as f:\n",
        "#   model_content = f.read()\n",
        "\n",
        "interpreter = tf.lite.Interpreter(model_content=tflite_streaming_model)\n",
        "interpreter.allocate_tensors()\n",
        "\n",
        "input_details = interpreter.get_input_details()\n",
        "output_details = interpreter.get_output_details()\n",
        "\n",
        "inputs = []\n",
        "for s in range(len(input_details)):\n",
        "  inputs.append(np.zeros(input_details[s]['shape'], dtype=np.float32))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "03QCq1nfVUWW",
        "outputId": "da360269-4cf8-4c76-fa1a-2e9d01a35bd9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([  1, 320], dtype=int32)"
            ]
          },
          "execution_count": 260,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "input_details[0]['shape']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "WKudF1Zyud2-"
      },
      "outputs": [],
      "source": [
        "sream_external_state_tflite_predicted_labels = []\n",
        "for input_data in train_data: # loop over all audio sequences\n",
        "  \n",
        "  # add batch dim - it is always 1 for streaming inference mode\n",
        "  input_data = np.expand_dims(input_data, axis=0)\n",
        "  \n",
        "  reset_state = True\n",
        "\n",
        "  # before processing new test sequence we can reset model state\n",
        "  # if we reset model state then it is not real streaming mode\n",
        "  if reset_state:\n",
        "    for s in range(len(input_details)):\n",
        "#       print(input_details[s]['shape'])\n",
        "      inputs[s] = np.zeros(input_details[s]['shape'], dtype=np.float32)\n",
        "\n",
        "  start = 0\n",
        "  end = flags.window_stride_samples\n",
        "  while end \u003c= input_data.shape[1]:\n",
        "    stream_update = input_data[:, start:end]\n",
        "    stream_update = stream_update.astype(np.float32)\n",
        "\n",
        "    # update indexes of streamed updates\n",
        "    start = end\n",
        "    end = start + flags.window_stride_samples\n",
        "\n",
        "    # set input audio data (by default input data at index 0)\n",
        "    interpreter.set_tensor(input_details[0]['index'], stream_update)\n",
        "\n",
        "    # set input states (index 1...)\n",
        "    for s in range(1, len(input_details)):\n",
        "      interpreter.set_tensor(input_details[s]['index'], inputs[s])\n",
        "\n",
        "    # run inference\n",
        "    interpreter.invoke()\n",
        "\n",
        "    # get output: classification\n",
        "    out_tflite = interpreter.get_tensor(output_details[0]['index'])\n",
        "    #print(start / 16000.0, np.argmax(out_tflite), np.max(out_tflite))\n",
        "\n",
        "    # get output states and set it back to input states\n",
        "    # which will be fed in the next inference cycle\n",
        "    for s in range(1, len(input_details)):\n",
        "      # The function `get_tensor()` returns a copy of the tensor data.\n",
        "      # Use `tensor()` in order to get a pointer to the tensor.\n",
        "      inputs[s] = interpreter.get_tensor(output_details[s]['index'])\n",
        "\n",
        "    out_tflite_argmax = np.argmax(out_tflite)\n",
        "  sream_external_state_tflite_predicted_labels.append(out_tflite_argmax)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yWy_BiepFFSX",
        "outputId": "04cb4226-7b0c-421e-d80f-f83c2a64fbd8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "accuracy 93.5546875\n"
          ]
        }
      ],
      "source": [
        "# validate that accuracy in streaming mode with external states is the same with accuracy in non streaming mode\n",
        "stream_accuracy_tflite = np.sum(sream_external_state_tflite_predicted_labels==train_label)/len(train_label)\n",
        "print(\"accuracy \" + str(stream_accuracy_tflite * 100))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iyGfyt54h02Y"
      },
      "outputs": [],
      "source": [
        ""
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "conv_batch_norm_on_generated_data.ipynb",
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      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
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    "language_info": {
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      "file_extension": ".py",
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